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This paper proposes a low budget solution to detect and possibly track space debris and satellites in Low Earth Orbit. The concept consists of a space-borne radar installed on a cubeSat flying at low altitude and detecting the occultations of radio signals coming from existing satellites flying at higher altitudes. The paper investigates the feasibility and performance of such a passive bistatic radar system. Key performance metrics considered in this paper are: the minimum size of detectable objects, considering visibility and frequency constraints on existing radio sources, the receiver size, and the compatibility with current cubeSat's technology. Different illuminator types and receiver altitudes are considered under the assumption that all illuminators and receivers are on circular orbits. [ABSTRACT FROM AUTHOR]

The multipeaked correlation functions of binary offset carrier (BOC) modulated signals introduce an ambiguity threat into the code tracking. Several techniques have been proposed to solve this problem, such as a class of two-dimensional (2-D) tracking techniques, in which the spreading code and the subcarrier are tracked separately. In this paper, the key properties of correlation functions and the theoretical tracking performance analysis considering noise and multipath environments of the general 2-D tracking loop are studied. Exact explicit expressions, taking into account the effects of local subcarrier waveform mismatching and the front-end bandlimiting, are provided for the correlation function employed in 2-D tracking. From these expressions, the key characteristics of 2-D correlation functions such as the shape, coupling relation between dimensions, and the effects of bandlimiting can be clearly seen. Moreover, general theoretical methods to predict the performance of the 2-D tracking techniques under the multipath and noise environments are provided. The results obtained in this paper can facilitate investigations in the area of 2-D tracking technique parameter optimization and performance assessment. [ABSTRACT FROM PUBLISHER]

To navigate in global navigation satellite systems (GNSS) signal-challenged environment, for example, foliage canopy, urban canyon, indoor, etc., high-sensitivity GNSS receivers are usually preferred for the improved acquisition and tracking capabilities. The core of high-sensitivity GNSS receiver design is to extend integration time coherently, which is optimal for improving post-signal-to-noise ratio, mitigating multipath and cross-correlation false locks, and avoiding squaring loss. In GNSS data channels, extending integration time coherently requires the navigation message data bit wipe-off. For stand-alone high-sensitivity GNSS receivers, bit wipe-off is usually achieved by using estimation algorithms (i.e., bit decoding) rather than accessing external networks (i.e., bit aiding). In this paper, the maximum-likelihood (ML) bit decoding is used to estimate the data bit values for bit wipe-off. Furthermore, the benefits of using advanced tracking algorithms?vector tracking and inertial navigation system (INS)-assisted tracking (i.e., ultratight coupling of GNSS/INS)?to improve ML bit decoding and navigation performance are analyzed. Two vehicular navigation tests are performed in dense foliage and an urban canyon environment. In the context of global positioning system L1 C/A signals, the field test results show that vector tracking and ultratight coupling can improve the successful decoding rate by up to 40% depending on signal strength. This paper also demonstrates how the signal power-based correlator selection method can address high bit error-rate problems when ML bit decoding is used for bit wipe-off in the signal-challenged environment. After implementing this algorithm, the position and velocity accuracy of the stand-alone high-sensitivity GNSS receiver has been improved about 50% after extending coherent integration time from 20 to 100 ms in the vehicular navigation tests. [ABSTRACT FROM PUBLISHER]

The use of ground-based transmitters (so-called pseudolites) for outdoor and indoor navigation has been under consideration since the origin of the Global Positioning System (GPS). However, one significant limitation of the use of code division multiple access (CDMA) was immediately obvious: one CDMA transmitter signal interferes with another CDMA transmitter signal. This is called the ""near-far problem."" Different methods have been studied in order to mitigate such jamming. This paper presents a new mitigation method based on a principle that can be summed up as follows: the signal and a delayed replica of the signal are broadcast by a ground transmitter antenna. At the receiver stage, the replica signal is used to eliminate the interference caused by the direct signal. This is called the double transmission technique (DTT), and it presents interesting performance features regarding interference mitigation. A signal processing technique corresponding to this method is presented in this paper, considering a GPS L1 C/A-code pseudolite. Performance simulations are also presented. [ABSTRACT FROM AUTHOR]

The automatic dependent surveillance—broadcast (ADS-B) system adopts an open communication mode, and the lack of designed-in security measures in the ADS-B system makes it vulnerable to various types of attacks (jamming, spoofing, etc.). In view of the low-bandwidth and less-data-bit features of the ADS-B, this paper studies the integrity and authenticity of information by signing messages and proposes an ADS-B message authentication method based on certificateless short signature. This method uses short signature and does not require certificate management and has efficient performance. Compared with the existing approach, the computation costs of the proposed method in the signature phase are reduced by 1/2, and the signature length is reduced by 3/4. Additionally, we used the extended NS2 simulation platform to simulate 1090ES data link in different scenarios of the network; the simulation results show that our solution is suitable for minimum operational performance standard of ADS-B. [ABSTRACT FROM AUTHOR]

Random jitter or offset between the transmitter/receiver clocks is an important parameter that has to be accurately estimated for optimal detection of pulse position modulation (PPM) symbols for high-data-rate optical communications. This parameter, in general, is modeled as an unknown random quantity that depends on the clock drift between the transmitter/receiver clocks and the random motion between the transmitter and receiver stations. In this paper, we have modeled the time jitter for two scenarios—phase modulation jitter and frequency modulation jitter. The phase modulation jitter is modeled as a Gaussian random variable which is estimated with the help of a maximum a posteriori probability (MAP) estimator. The frequency modulation jitter is characterized as a random walk, and this leads to the modeling of the jitter as a state space variable in the context of a dynamical system. Since the observations are the photon counts in each slot of a PPM symbol (for both MAP estimation and tracking), the resulting dynamical model is highly nonlinear, and particle filters are employed for tracking the frequency modulation jitter. We evaluate the performance of both the maximum a posteriori estimators and the particle filters in terms of the relative mean-square error and probability of error. We conclude that with MAP estimation and particle filters that estimate/track the time offset, we achieve a significant performance gain in terms of probability of error as compared to systems that do not have a time synchronization system in place. [ABSTRACT FROM AUTHOR]

In helicopter satellite communication systems, the received signal is blocked by the helicopter rotor blades during propagation, incurring the unstableness of traditional methods of channel estimation due to unknown channel state. To this end, a joint occlusion detection and phase estimation algorithm is proposed by factor graph in this paper. For occlusion detection to acquire channel state, the occlusion channel model is established relying on a Markov chain with a priori blocking ratio, in which the probability distribution of the channel state is calculated by the proposed message-passing algorithm. To obtain the occlusion position and update the blocking ratio, a cross-correlation method is designed. Furthermore, a joint block detection and phase estimation algorithm is developed based on the proposed occlusion detection algorithm to realize phase estimation by iterative receiver, where occlusion detection, phase estimation, and decoding are performed in turn for one turbo iteration and the result of decoding is then sent back to the occlusion detection step for the next iteration. Simulation results show that the proposed algorithm is adaptive to the dynamical change in the blocking ratio and can achieve bit error rate performance that is close to the performance bounds based on perfect channel state. [ABSTRACT FROM AUTHOR]

Spread spectrum (SS) signal acquisition in satellite communication is a very computation intensive technique, which hinders the development of real-time spread spectrum signal acquisition. In this paper, in order to achieve real-time acquisition, we propose a multi-GPU based SS signal acquisition algorithm. First, sliding correlation, the computation kernel, is formulated and efficiently parallelized by CUDA. Second, a CUDA-enabled SS signal acquisition algorithm is implemented by adopting the CUDA-enabled sliding correlation. Third, a multi-GPU based algorithm is implemented by using multi-GPU programming. The performance is evaluated in a real SS telemetry system. Real-time acquisition is achieved in all cases by using a single K40 GPU. Furthermore, an average of 374.7 $\times$ speedup (max 473 $\times$) in 6 datasets is achieved when using four K40 GPUs. Good scalability is observed when varying the parameters. [ABSTRACT FROM AUTHOR]

In this paper, we examine the problem of target detection for the multistatic passive radar. Passive radar systems leverage the existing wireless sources, such as radio/TV stations and cellular signals that are referred to as illuminators of opportunity (IOs), to illuminate the environment and provide surveillance functions. Usually, these IO source signals are sparse or locally sparse in the frequency domain. We develop a passive multistatic detector by exploiting the sparsity or local sparsity of the IO signals. To improve the computational efficiency, two fast implementations of the proposed detector are also introduced. Simulation results show that the proposed approaches outperform the conventional passive detection methods that model the IO signals as unknown without any specific structures. [ABSTRACT FROM AUTHOR]

Wide area multilateration (WAM) estimates aircraft positions on the basis of time difference of arrival (TDOA) for air traffic control. To design the receiver positions, dilution of precision has been used. However, the conventional approach ignores failure in signal detection. Therefore, this paper proposes a novel WAM accuracy model for more realistic performance prediction. The proposed model employs a stochastic constellation, i.e., the constellation of available receivers virtually changes according to the signal detection performance. [ABSTRACT FROM AUTHOR]

This paper presents an innovative global navigation satellite system (GNSS) fault detection and exclusion approach for the adoption of satellite localization in the rail sector. Current global integrity monitoring systems cannot guarantee the safety level needed for such applications as train control where tolerable hazard rate in the order of 10−9/h is required. A new method, named two tiers, enabling to integrate local augmentation systems and global augmentation infrastructures, is presented. It is based on the comparison of single differences residuals among satellites for detecting signal in space (SIS) faults and double difference residuals among local augmentation stations and satellite-based augmentation systems ranging and integrity monitoring stations for detecting reference stations faults. GPS SIS faults described in literature and real GNSS raw data recorded on a train are taken into account. This study reports the performance analysis for the two-tiers approach carried out during relevant European projects. A test-bed architecture has been developed through the implementation of the algorithm in real time on a local augmentation operational center. Relevant performances have been tested on a rail track for validating the algorithm in real operative conditions. Significant results of the analysis are reported for SIS integrity assessment only. [ABSTRACT FROM AUTHOR]

This paper derives closed-form expressions for bistatic synthetic aperture radar (SAR) spatial resolution of a generalized system from the $k$ -space or the wavenumber domain. These spatial resolution equations have not previously appeared in the literature. From these equations, significant resolution is found in range and cross range, forecasting a forward-scatter bistatic SAR image when the elevation angles of each bistatic platform are significantly different. Simulation and laboratory tests demonstrated the forward-scatter resolution. [ABSTRACT FROM AUTHOR]

Both economic incentives and policy trends motivate the study of spectrum sharing between radar and wireless communications as a means to mitigate spectrum scarcity. This paper proposes a novel, temporal signal processing algorithm for a radar to mitigate interference from cyclostationary, linearly modulated digital communications (LMDC) interference such as orthogonal frequency division multiplexing (OFDM) or code division multiple access (CDMA). The proposed algorithm has the form of a novel whitening filter followed by a matched filter, and as such it optimizes the statistical deflection among the class of all linear detection filters. The derived cyclostationary whitening filter has equivalent mathematical representations as: 1) the form of a multiuser detector followed by an interference canceler, and 2) a frequency-shift (FRESH) filter. Performance results indicate that the derived cyclostationary whitener can produce signal-to-interference-plus-noise ratio (SINR) improvements ranging from negligible to up to $\text{20 dB}$ for the parameters used in this study. The cyclostationary whitener leads to the greatest SINR improvements when the interference-plus-noise is dominated by only a few LMDC signals, such as might occur in a near-far scenario. [ABSTRACT FROM AUTHOR]

In this paper, a time-frequency (TF) jammer mitigation algorithm based on a Kalman filter is proposed for global navigation satellite system (GNSS) receivers. A new state-space representation of the received signal is formed considering the rapidly changing characteristics of the jamming signal. Using the instantaneous frequency (IF) and chirp rate estimates obtained by the TF analysis, the proposed algorithm applies a Kalman filter for jamming signal estimation. The estimated jamming signal is then subtracted from the received data to remove the jammer signal. To cope with the time-varying accuracy in the jammer parameter estimates, the methods for adaptively adjusting the process and measurement noise variances using chirp rate estimates are described. Simulations are performed to verify the effectiveness of the proposed method for mitigating various types of jammers. The proposed approach improves the jammer signal removal performance by minimizing the effect of the Kalman filter model mismatch when compared to other techniques reported in the literature. [ABSTRACT FROM AUTHOR]

In some well-known passive localization methods, when the number of equations equals the number of unknown object coordinates, there arise finite number of possible solutions. A localization disambiguation technique is required to identify the correct solution in these cases. As an example, the exact solution of time-difference-of-arrival (TDOA) based equations for four receiver sites, leads to a couple of solutions with only one of them being the true target position. This ambiguity conventionally is resolved by using angle-of-arrival measurements or using an additional receiver site, which increase the cost and complexity of the system. In this paper, a localization disambiguation technique for a moving target based on sequential measurements is presented. In the proposed method, the correct solution corresponding to each measurement is identified by determining the most sensible path of the target. The method analytically finds the position of the target and no extra measurement/site is required. Performance of the proposed method has been evaluated and verified in numerous simulations as well as real data based on TDOA measurements. [ABSTRACT FROM AUTHOR]

In this paper, a Block Iterative Method with Adaptive Thresholding for Sparse Recovery (BIMATSR) is proposed to recover the received signal in an under-sampled distributed multiple-input multiple-output radar. The BIMATSR scheme induces block sparsity with the aid of a signal-dependent thresholding operator which increases the accuracy of the target parameter estimation task. We have proved that under some sufficient conditions, the suggested scheme converges to a stable solution. Moreover, different simulation scenarios confirm that the BIMATSR algorithm outperforms its counterparts in terms of the target parameter estimation. This superiority is achieved at the expense of slightly more computational complexity. It is also shown that in this application, random sampling scheme offers better performance than random Gaussian matrix, while it has simpler structure. [ABSTRACT FROM AUTHOR]

Tracking with bistatic sonar or radar measurements is challenging due to the fact that the measurements are nonlinear functions of the Cartesian state. The performance of existing approaches, including the extended Kalman filter and sigma point Kalman filters, such as the unscented Kalman filter and cubature Kalman filter, may not be acceptable in terms of mean square error or tracker consistency (i.e., the tracker's state estimation error covariance is not statistically consistent with the actual estimation errors). This paper generalizes the sigma point Kalman filter (SPKF) as a converted measurement SPKF. The resulting converted measurement sigma point Kalman filter is demonstrated to have improved performance over the conventional SPKF when employed in a bistatic tracking scenario. [ABSTRACT FROM AUTHOR]

This paper addresses the exploitation of Global Navigation Satellite Systems (GNSS) as transmitters of opportunity in passive bistatic radar systems for maritime surveillance. The main limitation of this technology is the restricted power budget provided by navigation satellites, which makes it necessary to define innovative moving target detection techniques specifically tailored for the system under consideration. To this aim, this paper puts forward long integration time techniques able to collect the signal energy over long time intervals (tens of seconds), allowing the retrieval of suitable levels of signal-to-disturbance ratios for detection purposes. A local plane based technique is first considered, providing target detection in a plane that represents the section of maritime area covered by the radar antenna. As a suboptimum solution in terms of achievable integration gain, but more efficient from a computational point of view, a second technique is considered working in the conventional bistatic range and Doppler plane (basic plane based). Results against synthetic and experimental datasets show the effectiveness of the proposed techniques. [ABSTRACT FROM AUTHOR]

Future space missions will be driven by factors such as the need for reduced cost of spacecraft without diminished performance, new services, and capabilities including reconfigurability, autonomous operations, target observation with improved resolution and servicing (or proximity) operations. Small satellites, deployed as a sensor network in space, can through intersatellite communication (ISC) enable the realization of these future goals. Developing the communication subsystem that can facilitate ISC within this distributed network of small satellites require a complex range of design tradeoffs. For small satellites, the general design parameters that are to be optimized for ISC are size, mass, and power, as well as cost (SMaP-C). Novel and efficient design techniques for implementing the communication subsystem are crucial for building multiple small satellite networks with capability for achieving significant data-rates along the intersatellite links (ISLs). In this paper, we propose an alternative approach to radio frequency and laser ISLs for ISC among small satellites deployed as a sensor network in low earth orbit. For short to medium range ISLs, we present an LED-based visible light communication (VLC) system that addresses the SMaP constraints, including capability for achieving significant data rates. Our research is focused on the development of the physical layer for pico-/nano class of satellites with prime consideration for the impact of solar background illumination on link performance. We develop an analytical model of the intersatellite link (ISL) in MATLAB and evaluate its feasibility and performance for different intensity modulation and direct detection schemes. Using a transmitted optical power of 4 W and digital pulse interval modulation, a receiver bandwidth requirement of 3.5 MHz is needed to achieve a data rate of 2.0 Mbits/s over a moderate link distance of 0.5 km at a BER of 10−6. [ABSTRACT FROM AUTHOR]

In this paper, we propose a low-complexity adaptive reduced-rank interference suppression scheme based on alternating low-rank decomposition techniques for navigation receivers. The proposed scheme, which employs a generalized sidelobe canceler structure, makes use of a projection matrix for rank reduction followed by a reduced-dimension receive filter. An alternating optimization strategy based on recursive least squares is devised to compute the basis vectors of the projection matrix and the receive filter adaptively. Simulation results show that the proposed algorithm achieves a better performance than existing methods with a reduced computational complexity. [ABSTRACT FROM AUTHOR]

This paper presents a novel filtering technique to estimate the position of a moving target based on discrete-time direction and velocity measurements. The velocity is assumed to be corrupted by an unknown constant bias, which is explicitly estimated in the process. A nonlinear system is first designed, describing the dynamics and observations associated to the target, followed then by a state augmentation that yields an equivalent linear time-varying system. An observability analysis for the latter is conducted based on necessary and sufficient conditions that are related to the target's motion. The final estimation solution resorts to a Kalman Filter with globally exponentially stable error dynamics. Its performance is assessed via realistic numerical simulations, including Monte Carlo runs and a comparison with both the standard extended Kalman filter and the Bayesian Cramér–Rao bound. A set of experimental results achieved within the scope of a realistic underwater mission scenario is also presented that allows to further assess the proposed technique. [ABSTRACT FROM AUTHOR]

In this paper, the distortion and defocus effects due to residual phase errors that are inherent in bistatic polar format algorithm are analyzed using time-domain Taylor series decomposition. A two-dimensional interpolation-based distortion correction method is developed, and accurate scene sizes limits are derived to mitigate the effects of defocus. The phase analysis is conducted with respect to arbitrary geometries, and examples are demonstrated for ideal linear and circular flight trajectories using a point target simulation. [ABSTRACT FROM AUTHOR]

A distributed multiple-input multiple-output (MIMO) radar system is capable of tracking multiple targets under the “defocused transmit-focused receive” (DTFR) operating mode, in which each transmitter forms a completely defocused beam to illuminate the whole surveillance region and each receiver adopts a focused beam to attain a higher resolution. However, when operating in this mode, there exists a resource optimization problem on the allocation of receive-beams. To address this problem, a receive-beam resource allocation (RBRA) strategy is proposed in this paper. The key mechanism is to implement the optimal allocation between receive-beams and targets based on the feedback information in the tracking recursion cycle, with the objective of improving the worst tracking accuracy with multiple targets. Since the posterior Cramér–Rao lower bound (PCRLB) provides a lower bound on the accuracy of target state estimates, it is derived and adopted as an optimization criterion. It is shown that the optimal RBRA is a multidimensional nonconvex assignment problem that is NP-hard. We propose an efficient convex relaxation optimization to solve it. Numerical results demonstrate the superior performance of the proposed strategy in terms of the worst case tracking root mean-square errors. [ABSTRACT FROM AUTHOR]

This paper presents results from experiments that utilize Global-Positioning-System-like terrestrial positioning signals in a passive radar system to track aircraft over a metropolitan area. Unlike communication signals, these positioning signals offer unique properties that are advantageous for a passive radar. Exploitation of these properties provides an opportunity to reduce hardware complexity and to enable passive radar systems with a lower cost. This paper provides a detailed description of the signal processing in the context of low-cost hardware. [ABSTRACT FROM AUTHOR]

Seminal bistatic inverse synthetic aperture radar (ISAR) work that was presented by Martorella et al. about a decade ago has demonstrated that an equivalent monostatic configuration can be used to approximate the bistatic configuration under certain constraints. This allows us to greatly simplify the signal processing that leads to the formation of a bistatic ISAR image. Nevertheless, when such constraints are not fully satisfied some distortions may be introduced. In this paper, such distortions are studied in detail and a reduction of them is proposed that is based on the use of superresolution techniques. [ABSTRACT FROM AUTHOR]

Probe-and-drogue refueling (PDR) is widely adopted owing to its simple requirement of equipment and flexibility, but it has an apparent drawback that the drogue position is susceptible to disturbances. There are three types of disturbances: atmospheric turbulence, trailing vortex of the tanker, and bow wave effect caused by the receiver. The former two disturbances are independent of the receiver, whereas the bow wave effect, which depends on the state of the receiver, greatly influences the docking within a close distance. As far as the authors know, little attention has been paid to the bow wave effect on docking control in existing literature. The existing literature related to the bow wave focuses on either qualitative static results obtained from experiments, or lookup tables based on computational fluid dynamics (CFD) analysis. These are inapplicable to the PDR docking controller design directly. This paper proposes a lower order dynamic model to describe drogue dynamics under the bow wave effect. The model consists of two components: one is a second-order transfer function matrix to describe the drogue dynamics, and the other is a nonlinear function vector to describe the bow wave effect model. A closed-loop simulation including the two components shows that the generated drogue dynamics are similar to those of a real experiment reported in an existing literature. [ABSTRACT FROM PUBLISHER]

Bistatic forward-looking synthetic aperture radar (BFSAR) is a kind of bistatic SAR (BiSAR) system that can image the forward-looking terrain in the flight direction of a receiver. Current literature and reports about BFSAR imaging are mainly concentrated on stationary scene imaging. In this paper, the ground moving target (GMT) theories for BFSAR are discussed. Firstly, the BFSAR signal models of a general GMT in both time-domain and Doppler-domain are shown. Meanwhile, the echo characteristics of the GMT are analyzed, which include the migration characteristic, the Doppler characteristic, the coupling characteristic, etc. After the above analysis, a GMT detection and imaging method for BFSAR is presented. The main purpose of the GMT detection method is to find out the difference between the GMT and the stationary background in an appropriate domain. However, for BFSAR, it is hard to do this since the relative movements between the BFSAR sensors and the GMT are strongly coupled, i.e., their respective influences cannot be easily separated. Different from the existing detection methods which use Doppler frequency (Doppler centroid) in Doppler-domain or space-time characteristics in space-time domain to differentiate the GMT from stationary background, the main idea of the method proposed in this paper is to distinguish the GMT from stationary background by their different Doppler frequency rates (DFRs) in DFR-domain. However, in order to do this, the stationary background?s DFRs must be equalized and the GMT?s DFR should be distinct from the same DFR of the stationary background. Then, the product second-order ambiguity function (PSAF) is used to detect and focus the GMT. Numerical simulations and experimental data processing verify the validity of the GMT theories and the method shown in this paper. [ABSTRACT FROM AUTHOR]

This paper presents a generalized theoretical analysis of Tsui's phase measurement approach for the situation in which there are N simultaneous signals, where one of the signals is strong and N - 1 signals are weak. Signal amplitudes are normalized to the amplitude of the strongest signal. This approach provides the capability to extract values of the signal parameters. The capability for up to N = 4 simultaneous signals is desired in the design goal for electronic warfare receivers. [ABSTRACT FROM AUTHOR]

In multipath environments, a global navigation satellite system (GNSS) receiver can obtain the most correct code phase estimate from the resolved first arrival path, which is expected to have the smallest excess delay (ED). However, because of the limited performance of the code phase discriminator, multipath interference (MI), and noise, the code phase estimate can be different from that of the true first arrival path. In this paper, we derive the statistical ED distribution and power delay spectrum of GNSS multipath components based on exponential scatterer distribution model (ESDM). In parallel, we investigate the ED distributions of the first arrival path, MI, and noise to develop mathematical expressions for the code phase estimation error (CPEE) distribution for wide, narrow, and strobe correlators in various multipath channels. The mathematical models of CPEE distributions have good match with the ESDM-based CPEE distributions and the CPEE distributions obtained from Monte Carlo simulations using the International Telecommunications Union Recommendations Section recommendation P.681-7 channel model. This paper introduces one of the first theoretical analyses and models of the GNSS CPEE distributions, which can provide insights into the CPEE in multipath environments and are essential to develop algorithms against multipath distortion. [ABSTRACT FROM AUTHOR]

This paper presents a physics-based, data-consistent, multifrequency GPS scintillation signal simulator. The simulator is based on the two-component power-law phase screen derived from real GPS scintillation measurements. The real data used to initialize the simulator, simulator outputs, and receiver-processed results are compared to demonstrate the simulator accuracy and the receiver processing effects. This simulator will enable better characterization of ionospheric scintillation effects and development of robust receiver algorithms during strong equatorial scintillation. [ABSTRACT FROM AUTHOR]

The received signal strength (RSS) of wireless signals conveys important information that has been widely used in wireless communications, localization, and tracking. Traditional RSS-based research and applications model the RSS signal using a deterministic component plus a white noise term. This paper investigates the assumption of white noise to have a further understanding of the RSS signal and proposes a methodology based on the Allan variance (AVAR) to characterize it. Using AVAR, we model the RSS unknown perturbations as correlated random terms. These terms can account for both colored noise or other effects such as shadowing or small-scale fading. Our results confirm that AVAR can be used to obtain a flexible model of the RSS perturbations, as expressed by colored noise components . The study is complemented by introducing two straightforward applications of the proposed methodology: the modeling and simulation of RSS noise using Wiener processes, and RSS localization using the extended Kalman filter. [ABSTRACT FROM AUTHOR]

In a recent paper, the problem of inverse synthetic aperture radar (ISAR) imaging moving ground targets was discussed and an effective solution based on a novel joint space-time adaptive processing (STAP)-ISAR formulation was proposed. In the case of bistatic geometry, ISAR imaging can be simply and effectively enabled via the bistatically equivalent monostatic theory, which allows for monostatic ISAR processing to be used to form bistatic ISAR images. However, the clutter nonstationary introduced by the bistatic geometry strongly degraded STAP performances if a monostatic STAP processing is used. In this paper, a new joint STAP-ISAR processing is introduced that works in the bistatic case. Theoretical figures and numerical simulations are used to prove the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Strong equatorial ionospheric scintillation of radio signals is often associated with simultaneous deep amplitude fading and rapid random carrier phase fluctuations. It poses a challenge for satellite navigation receiver carrier phase tracking loop operation. This paper presents a semi-open loop algorithm that utilizes the known position of a stationary receiver and satellite orbit information to estimate carrier phase variations during deep signal fading. Strong GPS scintillation data collected on Ascension Island in March 2013 are processed to reveal fast phase changes of half and full cycles over tens of milliseconds on all three GPS frequencies. Simulated signals are used to validate the algorithm and confirm that the fast phase changes are true scintillation effects rather than receiver processing artifacts. The algorithm performance is demonstrated through comparison with several closed-loop implementations. Potential errors associated with receiver clock bias and other environmental factors are also analyzed. A statistical summary of the concurrent fast phase changes and deep fades based on the processing results of the Ascension Island data is presented. [ABSTRACT FROM AUTHOR]

This paper is a first introduction to the concept of using global navigation satellite systems (GNSS) as illuminators of opportunity in a passive bistatic real-time radar system for maritime target indication applications. An overview of the system concept and the signal processing algorithms for moving target indication is provided. To verify the feasibility of the system implementation as well as test the developed signal processing algorithms, an experimental test bed was developed and the appropriate experimental campaign with the new Galileo satellites and a ferry as the target was carried out. The results confirm the system concept and its potential for multistatic operation, with the ferry being detected simultaneously by two satellites. [ABSTRACT FROM AUTHOR]

Accurate, reliable, and robust global positioning system (GPS) localization is desirable for many navigation applications. Unfortunately, it is challenging for a single GPS receiver to always provide accurate positioning solutions. In urban environments, intermittent signal availability leads to degraded GPS signal tracking and position estimation of the single GPS receiver. In addition, equipment malfunction of the single GPS receiver results in inaccurate navigation solutions. This paper presents a deeply coupled multireceiver vector tracking (MRVT) architecture that improves the reliability and robustness of GPS signal tracking and position estimation. MRVT jointly tracks GPS signals received by multiple GPS receivers, mitigating GPS signal tracking disruptions, improving the reliability of GPS localization in periods of intermittent signal availability. In addition, the MRVT receiver is more robust to equipment malfunctions than the single GPS receiver. We implemented an MRVT receiver using commercial radio frequency front ends and our PyGNSS software. We experimentally validated the reliability of our MRVT receiver in periods of intermittent GPS availability experienced in downtown San Francisco. Our MRVT receiver exhibited consistent GPS signal tracking and position estimation as compared to vector tracking. In addition, we experimentally validated the robustness of our MRVT receiver to the failure of a single GPS receiver. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a bistatic inverse synthetic aperture radar (Bi-ISAR) cross-range scaling (CRS) method to more effectively use Bi-ISAR images in their applications. For this, we propose a method to estimate the effective rotation velocity of a target in a Bi-ISAR imaging system, and restore a linear-geometry distortion that yields a sheared shape of Bi-ISAR images. In the simulations, we observed that our proposed method is capable of performing robust and precise Bi-ISAR CRS. [ABSTRACT FROM AUTHOR]

This paper presents the performance analysis and the optimizations of the generalized phase locked loop (PLL) and the generalized frequency locked loop (FLL). Using the minimum mean square error (MMSE) criterion as a performance measure, the optimal solutions for the generalized PLL and FLL designs under various scenarios: strong and weak signal strength, low and high dynamic, and good and poor oscillator quality are investigated. An adaptive PLL based on automatically adjustment of the integration time and loop parameters in an optimized manner is proposed. An adaptive FLL that operates with the optimal loop parameters is also presented. Simulation results demonstrate the effectiveness of the proposed generalized closed-loop tracking architecture and validate the proposed adaptive tracking schemes. [ABSTRACT FROM AUTHOR]

This paper investigates a new and special imaging mode, bistatic forward-looking high-speed maneuvering platform synthetic aperture radar, in which both platforms travel curvilinear trajectories with high velocities and accelerations. A thorough understanding of its new properties of motion, 2-D resolution, and echo signal coupling is given. Applicability of gradient method neglecting time dependence of gradient to this special configuration is addressed. Moreover, 2-D coupling characteristic of echo signal at different imaging distances is investigated. [ABSTRACT FROM AUTHOR]

In this paper, a weighted least squares (WLS) method is presented to find the location of a single target by the use of bistatic range (BR) measurements in multistatic passive radar. The proposed method is based on the idea of eliminating the nuisance parameter. Then, the method employs several WLS minimizations to obtain the target location estimate. The weighting matrix producing a significant improvement in the performance of the method is derived in two different conditions—one of them results in the maximum likelihood estimator (MLE) and the other one leads to the best linear unbiased estimator (BLUE). The accuracy properties of the method are analyzed, and the Cramer-Rao lower bound (CRLB) for target localization accuracy is also derived. In addition, in a two-dimensional space and in the case of localizing with one transmitter and the minimal number of receivers, the different placements of receivers are analytically determined, in each of which the location solution is not unique. Furthermore, from different aspects, the BR-based localization is compared to the hyperbolic localization derived from range difference (RD) measurements. [ABSTRACT FROM AUTHOR]

In this paper, improved signal processing techniques are developed for the analysis and classification of low probability of intercept (LPI) radar waveforms. The intercepted LPI radar signals are classified based on the type of pulse compression waveform. They are classified as linear frequency modulation, nonlinear linear frequency modulation, binary frequency shift keying, polyphase Barker, polyphase P1, P2, P3, P4, and Frank codes. The classification approach is based on the parameters measured from the preprocessed radar signal intercepted by electronic support (ES) or electronic intelligence (ELINT) system. First, signal embedded within the noise is estimated using Wigner Ville distribution to improve the signal-to-noise ratio (SNR). Next, features are extracted using the time-domain and frequency-domain techniques. Furthermore, parameters measured from the fractional Fourier transform are used for the classification. This type of techniques are required in various systems such as ES, electronic attack, radar emitter identification and multi input multi output (MIMO) radar applications. Extensive simulations are carried out with different LPI radar-modulated waveforms corrupted with additive white Gaussian noise of SNR up to –15 dB and impulse noise with 90% of noise density. The proposed algorithm outperforms the existing techniques of classification and can be used under strategic environment. [ABSTRACT FROM PUBLISHER]

In this paper, an approach for the design and analysis of coherent constant false alarm rate (CFAR) detectors in clutter and interference with a Kronecker covariance structure is described. In a two-dimensional example considered, the interference-plus-noise matrix \mathbf X \in \mathbbC^N \times L is modeled by a doubly correlated, zero-mean multivariate complex Gaussian distribution described by two covariance matrices \mathbf C and \mathbf R that are unknown to the receiver. The concatenated columns of \mathbf X has a structured covariance matrix \mathbf \Sigma given by {\mathbf \Sigma } = {\mathbf R}^{*} \otimes {\mathbf C}. In the approach described, an estimate of \mathbf R is used to “prewhiten” and match filter all the rows of both the training data matrices and the test data matrix. The processing enables one to reduce the detection problem to a one-dimensional case that can be handled by any one of the several adaptive detection algorithms. The proposed algorithm for the doubly correlated clutter is analyzed to show that the detection performance is determined by two statistically independent signal-to-interference-plus-noise loss factors both of which have complex beta distributions. Sample results show that the proposed approach requires training samples that is a multiple of N+L$, while an adaptive detection algorithm that do not explicitly use the Kronecker constraint on the covariance structure requires training samples that is a multiple of $N \times L$ for comparable detection performance. [ABSTRACT FROM PUBLISHER]

Geometry configuration is crucial to the system performance in distributed multiple-input–multiple-output (MIMO) radars. Sensor placement in distributed MIMO radars is different from the conventional sensor placement problem as transmitters and receivers need to cooperate with each other to perform sensing. In this paper, we establish a combinatorial optimization model for the joint placement of transmitters and receivers. The proposed algorithm first transforms the original model into an equivalent model with convex constraints via convex relaxation. Then, the nonconvex objective function is further replaced with a new convex surrogate. The surrogate is shown to converge to a good approximation of the original optimal solution. The performance of the proposed algorithm is validated using numerical simulations. [ABSTRACT FROM AUTHOR]

Chirp signals arise in many applications of signal processing. In this paper, we address the problem of detection of chirp signals that are encountered in a bistatic radar which we are developing for remote sensing of cosmic ray induced air showers. The received echoes from the air showers are wideband and characterized by very short sweep periods. This makes our astrophysical problem a challenging one, since a very short sweep period is equivalent to a very low energy chirp signal. Furthermore, the related parameters of the received echoes are nondeterministic since they are tied to the physical parameters of the air showers. The primary focus of this research is to address these challenges and to find an optimized detection approach in the additive white Gaussian noise channel for low signal-to-noise ratio (SNR) levels. Matched filters are commonly used in the radar systems when the chirp signal is known. In this paper, we revisit this context and use a “matched filter” as a basis of building a rake-like receiver which consists of a set of filters matched to quantized chirp rates, logarithmically distributed within the chirp-rate interval of interest. We examine the detection capability of the proposed structure through extensive theoretical and numerical analysis. Theoretical analysis and simulation results prove that the proposed detector has high detection capability for a range of chirp slopes in a low-SNR environment. [ABSTRACT FROM AUTHOR]

Modern global navigation satellite system (GNSS) front ends sample the received radio-frequency signal at an intermediate frequency (IF) and, then, downconvert it to baseband in the digital domain. A locally generated spreading code is subsequently correlated with the baseband signal at the sampling frequency. This can mean that the receiver correlates at an unnecessarily high frequency (sometimes more than four times the chipping rate). The power consumption is, thus, high. If the baseband signal is downsampled after appropriate filtering, the correlator can process at a fraction of the sampling frequency. The power dissipation is considerably reduced as a result. Furthermore, by resampling at an integer submultiple of the sampling frequency, not only is downsampling jitter eliminated, but also architectural configurability in the correlator is possible, allowing further reductions in power and resource consumption. In this paper, a dynamically configurable decimator for a matched filter correlator is presented. The mathematical model of the signal processing is analyzed for various downsample rates. The effective postcorrelator signal-to-noise-plus interference ratio is estimated in theory and measured by experiment, illustrating that the proposed decimator correlator outperforms the resample IF correlator. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the achievable coverage and the information rate of an aerial base station. The air-to-ground link is analysed by considering random fading and shadowing effects impairing the wireless transmission, together with a homogeneous spatial distribution of the terrestrial users. The distribution of the buildings in the underlying coverage region is modeled using the International Telecommunication Union-Recommendation statistical city model. For a given urban environment/region, we analytically quantify the achievable coverage probability and the information rate of users on the ground at a particular base station altitude. Furthermore, we analytically find the optimal altitude of the aerial base station to maximise the terrestrial coverage given a certain service region. Simulations are conducted to verify our analysis, and a close match between the analytical and simulation results is observed. [ABSTRACT FROM AUTHOR]

With the proliferation of GPS-enabled mobile devices, location based services have gained in popularity. In particular, proximity-based services are commonly used to help a user interact with other users nearby. However, these services endanger the privacy of users as the location information is provided to the service provider. This paper proposes a novel private proximity detection scheme based on partial GPS range measurement information. We develop an efficient algorithm for proximity detection and theoretically analyze the false alarm performance. Simulation and empirical results validate this scheme and evaluate its performance. [ABSTRACT FROM AUTHOR]

Satellite navigation is quickly becoming a multidimensional complex challenge, with four Global Navigation Satellite Systems (GNSS) fully or partially deployed, more than 90 GNSS satellites currently in the sky, and 12 open-service GNSS signal types available to the end-user. Research papers about GNSS performance typically focus on single or dual GNSS solutions, and there are still very few papers addressing jointly the four existing GNSS together. It is the goal of our paper to present a unified, fast, modular, and simple-to-program theoretical analysis of the four GNSS, focusing on performance limits in terms of spectral characteristics, tracking, multipath robustness, and positioning accuracy. A unified new compact approach for dealing with all the modulations employed in GNSS is also included.We show a unified generic framework for analyzing the multi-GNSS signals in a fast and simple-to-implement manner, without the need of simulating constellations or gathering measurement data. Our approach is also validated with Spectracom-based constellation data. Our analysis can be used as the starting point in further design process or system analysis. [ABSTRACT FROM AUTHOR]

This paper considers the localization of a moving target using a forward scatter radar consisting of a transmitter and an array antenna receiver. A direct positioning method based on maximum likelihood (ML) estimation is proposed and compared with the conventional two-step method in which the primary parameters, including Doppler shift and angle of arrival, should be determined in the first step. Moreover, closed-form expressions for Cramer–Rao lower bound of both methods are derived. The aforementioned methods are comprehensively compared in terms of positioning accuracy and computational complexity. Theoretical performance study, including determining the minimum required observation time for achieving a certain positioning error level and analyzing the best possible positioning accuracy in extreme scenarios, is carried out. The results of numerical simulations demonstrate that the proposed direct approach is more precise compared to the two-step method and can achieve higher resolution levels. [ABSTRACT FROM AUTHOR]

In this paper, the detection of LoRa signals from a low-earth orbit (LEO) satellite is considered. The use of a LEO satellite to collect messages from the terminals, as an alternative to terrestrial base stations in rural areas, represents a major challenge due to the specific impairments of this scenario, e.g., Doppler effects and interfering signals. A redesign, whose validation is assessed through a system simulator operating in a realistic scenario, is thus required. [ABSTRACT FROM AUTHOR]

In this paper, a generalized signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. The derived model is then used to define a MIMO ambiguity function based on the Kullback–Leibler divergence. Moreover, the proposed formulation is parametrized using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modeling approach. A comparison between the proposed definition and the more conventional approach of summing the squared matched filter outputs is presented for different sensors and waveforms configurations. [ABSTRACT FROM AUTHOR]