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Multistatic imaging systems are commonly used in radar systems and microwave imaging. In these systems, many antennas are arranged three-dimensionally and connected to RF switches. The length of each transmitter (Tx) and receiver (Rx) channel differs slightly, causing artifacts in high-resolution image reconstruction. This study presents a novel method for the phase calibration of multistatic systems. This method does not require system reconstruction and can automatically perform phase calibration in a short time. This method is expected to facilitate an accurate phase measurement in multistatic systems. The approach involves phase calibration by analyzing the reflection coefficients of antenna elements in the time domain. Imaging experiments were performed on a multistatic imaging system using this calibration method, and the position and shape of a metal rod with a diameter one-fourth of a wavelength were reconstructed by simple back-projection with an accuracy beyond the diffraction limit. [ABSTRACT FROM AUTHOR]

A novel multistatic integrated sensing and communication (ISAC) system based on macro–micro cooperation for the sixth-generation (6G) mobile network is proposed. Instead of using macrosites at both the transmitter and receiver sides, microsites are considered as receivers in cooperative sensing. This system is important since microsites can be deployed more flexibly to reduce their distances to the sensing objects, providing better coverage for sensing service. In this work, we first analyze the deployment problem of microsites, which can be deployed along the radius and azimuth angle to cover macrosite cells. The coverage area of each microsite is derived in terms of its position in the cell. Then, we describe an efficient estimating approach for obtaining the position and velocity of sensing objects in the macrosite cell. By choosing multiple microsites around the targeted sensing area, joint data processing with an efficient optimization method is also provided. Simulation results show that the multistatic ISAC system employing macro–micro cooperation can improve the position and velocity estimation accuracy of objects compared to systems employing macrosite cooperation alone, demonstrating the effectiveness and potential for implementing the proposed system in the 6G mobile network. [ABSTRACT FROM AUTHOR]

Radar networks offer the possibility to overcome the limitations of single sensors. However, without coherent signal processing, the full potential of radar networks cannot be exploited. Therefore, the synchronization of independent radar sensors is crucial in order to mitigate performance degradation due to frequency deviations of uncoupled reference oscillators. Systematically derived synchronization criteria for coupling-induced errors such as sampling frequency offset (SFO), carrier frequency offset (CFO) and symbol timing offset (STO) of uncoupled orthogonal frequency-division multiplexing (OFDM) radar sensors enable to determine hardware specifications, such as the required reference oscillator frequency stability. This aids in the design of digital radar networks and ensures error-free signal processing in advance. The concept of deriving said criteria is applicable to other modulation types used for digital radar sensors. Additionally, signal processing-based error estimation and correction methods are presented. By exploiting standard radar images, namely range profiles and range-Doppler images, the proposed methods estimate and correct any occurring SFO, CFO and STO. Furthermore, by applying the signal processing synchronization methods, they allow for a more lenient radar network design. Measurements using a 77 GHz digital radar demonstrator verify the derived criteria and error estimation and correction methods.

Multistatic imaging systems are commonly used in radar systems and microwave imaging. In these systems, many antennas are arranged three-dimensionally and connected to RF switches. The length of each transmitter (Tx) and receiver (Rx) channel differs slightly, causing artifacts in high-resolution image reconstruction. This study presents a novel method for the phase calibration of multistatic systems. This method does not require system reconstruction and can automatically perform phase calibration in a short time. This method is expected to facilitate an accurate phase measurement in multistatic systems. The approach involves phase calibration by analyzing the reflection coefficients of antenna elements in the time domain. Imaging experiments were performed on a multistatic imaging system using this calibration method, and the position and shape of a metal rod with a diameter one-fourth of a wavelength were reconstructed by simple back-projection with an accuracy beyond the diffraction limit.

Multirotor Unmanned Air Systems (UAS) represent a significant improvement in capability for Synthetic Aperture Radar (SAR) imaging when compared to traditional, fixed-wing, platforms. In particular, a swarm of UAS can generate significant measurement diversity through variation of spatial and frequency collections across an array of sensors. In such imaging schemes, the image formation step is challenging due to strong extended sidelobe; however, were this to be effectively managed, a dramatic increase in image quality is theoretically possible. Since 2015, QinetiQ have developed the RIBI system, which uses multiple UAS to perform short-range multistatic collections, and this requires novel near-field processing to mitigate the high sidelobes observed and form actionable imagery. This paper applies a number of algorithms to assess image reconstruction of simulated near-field multistatic SAR with an aim to suppress sidelobes observed in the RIBI system, investigating techniques including traditional SAR processing, regularised linear regression, compressive sensing. In these simulations presented, Elastic net, Orthogonal Matched Pursuit, and Iterative Hard Thresholding all show the ability to suppress sidelobes while preserving accuracy of scatterer RCS. This has also lead to a novel processing approach for reconstructing SAR images based on the observed Elastic net and Iterative Hard Thresholding performance, mitigating weaknesses to generate an improved combined approach. The relative strengths and weaknesses of the algorithms are discussed, as well as their application to more complex real-world imagery. [ABSTRACT FROM AUTHOR]

With radar networks, the resolution of critical radar parameters such as Doppler and angle can be improved compared to a single radar sensor. As the network’s aperture is considerably larger than that of a single radar, a much higher angular resolution is achieved. However, with a large aperture, range-dependent phase deviations, that is, near-field effects, occur and affect the angle estimation. In this work, these near-field effects are evaluated exemplarily for a coherent network. Furthermore, a new strategy to compensate for those network near-field effects is proposed and demonstrated based on measurements. The benefits of the near-field compensation are emphasized by comparing the network’s angle-estimation capabilities with and without compensated near-field effects. [ABSTRACT FROM AUTHOR]

High-performance millimeter-wave (mm-wave) multiple-in-multiple-out (MIMO) radars have been using efficient multiplexing with increasingly complicated radar waveforms, where conventional hardware architectures suffer from inevitably high design complexity and cost. This article presents a new software-defined mm-wave multistatic imaging system which provides great efficiency and flexibility to generate and process complicated radar waveforms. A general system block diagram and its signal model are proposed to use space-time-coded orthogonal frequency-division multiplexing (OFDM) for simultaneous MIMO transmission at the same time and frequency. The space-time coding (STC) is designed based on the Hadamard matrix which allows simple decoupling and decoding for imaging processing. A radar prototype is designed to validate the proposed system architecture, which operates at 83.5 GHz with a frequency bandwidth of 4.8 GHz. The mm-wave front-end consists of a metal-printed 8-by-8 waveguide array with a small element-separation of 9 mm to form 64 virtual channels for three-dimensional imaging. Experimental results show good imaging performance, giving great potential to design future cost-effective high-performance mm-wave imaging with efficient multiplexing. [ABSTRACT FROM AUTHOR]

In recent years, the research of multistatic synthetic aperture radar (SAR) has become a hot spot because of its great potentials in military and civil applications. However, it is inevitably disturbed by electronic countermeasures. In the multistatic SAR image, the false target caused by transmitting deceptive jamming leads to misjudgment of the image information. In this article, a new antideceptive jamming method for multistatic SAR is proposed. This method can locate the deceptive jammer and effectively suppress it. First of all, the echo model of multistatic SAR in the jamming environment is set up. Based on this model, the relationship expression for the location of jammer is derived. Then, we use the maximally stable extremal region method and the Euclidean-distance-based method to detect and identify false target in the multistatic SAR image. By using the location information of false target, receivers, and transmitters, the expression of the jammer localization is solved to locate the jammer. Finally, the minimum variance distortionless response beamforming method and image mosaic method are used to effectively suppress the jamming. The simulation results show that the method is effective.

Abstract With the recent increase in numbers of small and versatile low-power meteor radars, the opportunity exists to benefit from simultaneous application of multiple systems spaced by only a few hundred km and less. Transmissions from one site can be recorded at adjacent receiving sites using various degrees of forward scatter, potentially allowing atmospheric conditions in the mesopause regions between stations to be diagnosed. This can allow a better spatial overview of the atmospheric conditions at any time. Such studies have been carried out using a small version of such so-called multistatic meteor radars, e.g. Chau et al. (Radio Sci 52:811–828, 2017, https://doi.org/10.1002/2016rs006225). These authors were able to also make measurements of vorticity and divergence. However, measurement uncertainties arise which need to be considered in any application of such techniques. Some errors are so severe that they prohibit useful application of the technique in certain locations, particularly for zones at the midpoints of the radars sites. In this paper, software is developed to allow these errors to be determined, and examples of typical errors involved are discussed. The software should be of value to others who wish to optimize their own MMR systems.

Microwave/millimeter-wave imaging has a wide prospect in applications of concealed weapons detection. The main problem of the existing techniques lies in the contradiction between the imaging speed and the system cost. In this respect, a cylindrical sparse multiple-input–multiple-output (MIMO) array topology is proposed, which has no mechanical scanning so as to achieve fast sampling process. Furthermore, it can provide more angular observations than the mainly used systems with a planar aperture. To speed up the image reconstruction process, a phase center approximation-based transformation is made to convert the multistatic sampling scheme to its monostatic counterpart for which there are more fast and tractable imaging algorithms. Then, a phase calibration method is presented after we analyze the error of such an equivalence. In so doing, the cylindrical MIMO topology is transformed into an approximate monostatic one. Finally, a wavenumber domain algorithm is employed to attain the fast image reconstruction. Numerical simulations are provided to demonstrate the performance improvement of the proposed technique. [ABSTRACT FROM AUTHOR]

The high-frequency radar coastal network in Toulon operates in multistatic mode for the monitoring of the ocean circulation in the Northwestern Mediterranean Sea. With 2 transmitters and 2 receivers on 3 distant sites, it measures 4 different elliptical components of the surface velocity. We provide a methodology for improved current mapping using this augmented number of available projections and we show some typical results obtained during the year 2019. The validity and the quality of the reconstruction are assessed through comparisons with two types of in situ measurements, namely drifters' velocities from a dedicated campaign and acoustic Doppler current profiler data from an opportunity oceanographic campaign. The results of these assessments confirm the accuracy of these high-frequency radar measurements and their ability to capture the meso- to submeso-scale variability of the near shelf circulation. [ABSTRACT FROM AUTHOR]

Ground-penetrating radar (GPR) is a widely popular sensing method with broad applications in nondestructive subsurface imaging. This article presents a multistatic GPR for vehicle-mounted roadway and utility monitoring applications that employ several methods to improve performance compared with the state of the art. The proposed system illuminates the subsurface with pseudorandom codes (m-sequences) that have near-ideal autocorrelation properties. As a result, the received signal can be matched-filtered to provide pulse compression, which improves both range resolution and depth of scan compared with impulse-based GPRs. It also uses a highly digital transmit and receive architecture based on direct FPGA-based transmit pulse generation and direct radio frequency (RF) sampling of the received echoes. Furthermore, the analog front end uses an $8 \times 8$ multistatic antenna array design with broadband antipodal Vivaldi elements to provide spatial diversity, which leads to the improved object localization and reduced drift between scans. Experimental results from indoor and outdoor test beds confirm the functionality of the proposed GPR system. [ABSTRACT FROM AUTHOR]

Ground-based synthetic aperture radar (GB-SAR) is a useful tool to simulate advanced SAR systems with its flexibility on RF system and SAR configuration. This paper reports an indoor experiment of bistatic/multistatic GB-SAR operated in Ku-band with two antennae: one antenna was stationary on the ground and the other was moving along a linear rail. Multiple bistatic GB-SAR images were taken with various stationary antenna positions, and then averaged to simulate a multistatic GB-SAR configuration composed of a moving Tx antenna along a rail and multiple stationary Rx antennae with various viewing angles. This configuration simulates the use of a spaceborne/airborne SAR system as a transmitting antenna and multiple ground-based stationary antennae as receiving antennae to obtain omni-directional scattering images. This SAR geometry with one-stationary and one-moving antennae configuration was analyzed and a time-domain SAR focusing algorithm was adjusted to this geometry. Being stationary for one antenna, the Doppler rate was analyzed to be half of the monostatic case, and the azimuth resolution was doubled. Image quality was enhanced by identifying and reducing azimuth ambiguity. By averaging multiple bistatic images from various stationary antenna positions, a multistatic GB-SAR image was achieved to have better image swath and reduced speckle noise.

Multistatic or distributed satellite systems offer new and unique capabilities necessary for Earth observation with high spatial and temporal resolution. This letter describes a multistatic synthetic aperture radar (SAR) experiment employing the satellites TerraSAR-X and TanDEM-X. In order to demonstrate distributed SAR imaging from space, special data acquisitions with a dedicated geometry were performed. The data evaluation approach is outlined and azimuth profiles over a region with high-contrast backscatter are used to evaluate the azimuth signal reconstruction performance. The results are verified with simulations performed with a flexible SAR simulator reproducing the acquired scene. Finally, the effect of target motion on the reconstruction is analyzed and discussed based on the experimental data. [ABSTRACT FROM AUTHOR]

A multistatic system uses a transmitter to illuminate the object of interest and collects the reflected signal by a number of receivers to determine its location. In some scenarios such as passive coherent localization or for gaining flexibility, the position of the transmitter is not known. This paper investigates the use of the indirect path measurements reflected off the object alone, or together with the direct path measurements from the transmitter to receivers for locating the object in the absence of the transmitter position. We show that joint estimation of the object and transmitter positions from both the indirect and direct measurements can yield a better object location estimate than using the indirect measurements only by eliminating the dependency of the transmitter position. An algebraic closed-form solution is developed for the nonlinear problem of joint estimation and is shown analytically to achieve the Cramér–Rao lower bound performance under Gaussian noise over the small error region. To complete the study and gain insight, the optimal receiver placement in the absence of transmitter position is derived by minimizing the estimation confidence region or the mean-square estimation error for the object location. The performance lost due to unknown transmitter position under the optimal geometries is quantified. Simulations confirm well with the theoretical developments. [ABSTRACT FROM AUTHOR]

We present a novel imaging method for compact low-profile imagers in millimeter wave (mmW) and terahertz (THz) frequencies. The method borrows the principles of computerized tomography to generate 2-D or 3-D high-resolution images using simplified RF front ends. To perform imaging, the proposed scheme implements the projection-slice theorem. Specifically, it records the Radon transform (RT) of the desired field-of-view (FOV) and reconstructs the image using the Fourier slice theorem. To achieve the illumination of the FOV, the proposed imaging configuration uses a rotating linear antenna array that produces a highly directive fan beam. The antenna elements are further reduced using multistatic sparse array techniques without compromising the image reconstruction process. By dramatically reducing the number of active elements, the new method could allow high-resolution mmW/THz imaging systems to be embedded in low profile and lightweight platforms, including unmanned aerial vehicles or CubeSats. In this paper, we present the basic concept of the novel imaging scheme and simulation results verifying the proof of concept. Finally, we present a modified imaging antenna array that alleviates interference from objects and sources outside the FOV. [ABSTRACT FROM AUTHOR]

Multiple-input-multiple-output (MIMO) radar image processing presents problems difficult to address by modifying conventional monostatic radar methods as Fourier range migration. When the distance between the transmitter and receiver is comparable to the target size, the single phase center approximation is not accurate. Furthermore, if the antenna radiation pattern significantly deviates from a spherical wave, the symmetries assumed in most range migration techniques are violated. We present a rapid Fourier-based MIMO reconstruction called Fourier accelerated multistatic imaging (FAMI) suitable for massively parallel computation that accounts for frequency-dependent radiation patterns, does not require the single phase center approximation, and is able to dynamically adapt to different target support volume shapes. FAMI is especially suitable for frequency-diversity antenna systems that use spectrally modulated coded spatial radiation patterns.

This paper addresses some of the existing research gaps in the practical use of acoustic waves for navigation of autonomous air and surface vehicles. After providing a characterisation of ultrasonic transducers, a multistatic sensor arrangement is discussed, with multiple transmitters broadcasting their respective signals in a round-robin fashion, following a time division multiple access (TDMA) scheme. In particular, an optimisation methodology for the placement of transmitters in a given test volume is presented with the objective of minimizing the position dilution of precision (PDOP) and maximizing the sensor availability. Additionally, the contribution of platform dynamics to positioning error is also analysed in order to support future ground and flight vehicle test activities. Results are presented of both theoretical and experimental data analysis performed to determine the positioning accuracy attainable from the proposed multistatic acoustic navigation sensor. In particular, the ranging errors due to signal delays and attenuation of sound waves in air are analytically derived, and static indoor positioning tests are performed to determine the positioning accuracy attainable with different transmitter–receiver-relative geometries. Additionally, it is shown that the proposed transmitter placement optimisation methodology leads to increased accuracy and better coverage in an indoor environment, where the required position, velocity, and time (PVT) data cannot be delivered by satellite-based navigation systems.

A fully automatic time-domain measurement system for ultra-wideband (UWB) microwave imaging is presented. The system uses a pair of movable antennas to transmit and receive custom UWB pulse designs with each antenna able to be independently controlled to rotate about a region of interest. A full measurement, consisting of both incident and total field collections, is completed within 20 min using custom software. The collected data is processed to reconstruct images of three test objects. Imaging results demonstrate the system can localize and recognize different shaped objects, and differentiate multiple objects. The precision of antenna positioning and the impact of random noise on the microwave signal are investigated. The maximal positioning error for the antennas allows for accurate use of the system up to 7 GHz. A comparison between the time-domain system and a frequency-sweep method shows both methods allow for accurate imaging results. The signal-to-noise ratio and image quality may be improved with time-domain results when properly selecting a time window for the received signal. [ABSTRACT FROM PUBLISHER]

Distributed inverse synthetic aperture radar (ISAR) exploits the data acquired by multiple radar sensors carried by multiple platforms working in formation to increase the cross range resolution with respect to the value achievable by single platform systems. In this frame, the paper addresses the problem of the estimation of the ship dynamics, i.e., yaw, pitch, and roll rotation motions, exploiting the signals collected by such multiplatform radar imaging systems providing angular diversity in order to enable the focusing of the distributed ISAR images. Specifically, in this work a multi-angle formation of sensors is considered and the corresponding maximum likelihood estimator and Cramer Rao bound are derived. Then, a new Doppler matching based technique is proposed as a suboptimal approach exploiting only the linear component of the phase of the received signals. The performance analysis proves the effectiveness of the proposed techniques to separately estimate the horizontal, radial, and vertical components of the rotation vector, therefore making possible both the focusing and accurate cross-range scaling of the distributed ISAR products (as well as of the low-resolution ISAR images regarding the different sensors) and, as a further advantage, providing knowledge of the orientation of the corresponding image projection planes. The analysis of experimental multisensor datasets confirms the feasibility of the proposed techniques. [ABSTRACT FROM AUTHOR]

The study investigates underwater multi-target tracking (MTT) in a multistatic system using autonomous underwater vehicles (AUVs) as receivers separately from transmitters. The most critical aspect of MTT is the accurate extraction of target tracks from the collected measurements, which can be affected by clutter, missed detections, and port-starboard ambiguities. Moreover, the detection parameters—the target-detection probability and clutter rate—used in MTT methods are typically unknown and change with varying environmental conditions and geometric distributions of the AUV, target, and sound transmitter. In view of these challenges, we propose a robust multi-sensor Poisson Multi-Bernoulli Mixture (R-MS-PMBM) filter immune to unknown detection parameters that treats clutter rates and detection probabilities as continuous random variables modeled by beta and gamma distributions, respectively. The R-MS-PMBM filter is a conjugate prior, and its closed form is derived. We introduce a measurement-driven adaptive birth model to initiate target tracks quickly and efficiently. Furthermore, a suboptimal Gibbs sampler is used to reduce the computational complexity of its practical implementation. The simulation results show that the proposed filter is resilient to unknown detection parameters and can effectively perform in challenging underwater scenarios. • This paper proposes a robust multi-sensor Poisson Multi-Bernoulli Mixture (R-MS-PMBM) filter for multi-target tracking (MTT) using autonomous underwater vehicles (AUVs) equipped with linear hydrophone arrays as passive receivers in challenging underwater scenarios. • The primary construction method introduces AUVs' detection parameters (target detection probability and false alarm rates) as continuous random variables and is proved to be conjugate. It is immune to the unknown and time-varying detection parameters and can learn and estimate detection parameters online to accurately extract the number and target tracks. • Without prior information on targets, the method applies an efficient and adaptive measurement-driven target birth model to initiate new target tracks based on all measurements efficiently. • As a result of the Monte Carlo sampling technique with minimum Markov property, the complexity of the method scales linearly with the number of AUVs, making the tracking system highly scalable. [ABSTRACT FROM AUTHOR]

How to obtain high-resolution images of ship targets is an active research area in radar field due to the complexity of the ship motion. At the same time, multi-platform based surveillance and combat mode is gaining more and more interests in recent years. Based on the above situation, in this paper, a multistatic Inverse Synthetic Aperture Radar (ISAR) ship imaging method is presented, the method is capable of increasing the integration time for stationary imaging by deploying the multiple platforms with appropriate altitudes and aspect angles and coherently integrating the echoes received by each platform. Combined with the optimal imaging time selection scheme, this method can obtain side-view or top-view ship images with higher-resolution as compared to the monostatic radar. Simulations are performed to verify the effectiveness of our multistatic ISAR ship imaging method.

Radar systems, based on bistatic radar concept attracted a substantial attention in the recent years. Passive coherent location systems using "transmitters of opportunity" like radio or TV broadcasters, GSM base stations, satellite communication and GNSS signals proved their potential in detection and tracking moving targets over a significant area. In this paper the multistatic location system with non-cooperative transmitters is described and various aspects of signal processing and signal parameters are discussed.

This paper investigated the feasibility for improved detection of human respiration using data fusion based on a multistatic ultra-wideband (UWB) radar. UWB-radar-based respiration detection is an emerging technology that has great promise in practice. It can be applied to remotely sense the presence of a human target for through-wall surveillance, post-earthquake search and rescue, etc. In these applications, a human target's position and posture are not known a priori. Uncertainty of the two factors results in a body orientation issue of UWB radar, namely the human target's thorax is not always facing the radar. Thus, the radial component of the thorax motion due to respiration decreases and the respiratory motion response contained in UWB radar echoes is too weak to be detected. To cope with the issue, this paper used multisensory information provided by the multistatic UWB radar, which took the form of impulse radios and comprised one transmitting and four separated receiving antennas. An adaptive Kalman filtering algorithm was then designed to fuse the UWB echo data from all the receiving channels to detect the respiratory-motion response contained in those data. In the experiment, a volunteer's respiration was correctly detected when he curled upon a camp bed behind a brick wall. Under the same scenario, the volunteer's respiration was detected based on the radar's single transmitting-receiving channels without data fusion using conventional algorithm, such as adaptive line enhancer and single-channel Kalman filtering. Moreover, performance of the data fusion algorithm was experimentally investigated with different channel combinations and antenna deployments. The experimental results show that the body orientation issue for human respiration detection via UWB radar can be dealt well with the multistatic UWB radar and the Kalman-filter-based data fusion, which can be applied to improve performance of UWB radar in real applications. [ABSTRACT FROM AUTHOR]

The maximum-likelihood probabilistic data association (ML–PDA) tracker and the maximum-likelihood probabilistic multihypothesis (ML–PMHT) tracker are tested in their capacity as algorithms for very low observable (VLO) targets (meaning 6-dB postsignal processing or even less) and are then applied to five synthetic benchmark multistatic active sonar scenarios featuring multiple targets, multiple sources, and multiple receivers. Both methods end up performing well in situations where there is a single target or widely spaced targets. However, ML–PMHT has an inherent advantage over ML–PDA in that its likelihood ratio (LR) has a simple multitarget formulation, which allows it to be implemented as a true multitarget tracker. This formulation, presented here for the first time, gives ML–PMHT superior performance for instances where multiple targets are closely spaced with similar motion dynamics. [ABSTRACT FROM AUTHOR]

Multistatic radar systems with several transmitters and receivers introduce not only new qualities in area surveillance as well as in hardware minimization but also new problems in signal processing and target detection and tracking. This paper deals with multistatic radar system consisting of several independent bistatic radars processing signals scattered of surrounding objects. The measured data, e.g. time delays and Doppler frequencies at individual radar are therefore not associated with a particular target. An optimal detection method should find the proper associations among a great number of their possible combinations. In this paper a detection method, based on a probability hypothesis density function (PHDF) is described and tested using a mathematical simulation in Matlab.

This paper addresses relativistic effects in bistatic and multistatic synthetic aperture radar (SAR) systems and missions. It is shown that the use of different reference frames for bistatic SAR processing and bistatic radar synchronization is prone to notable phase and time errors. These errors are a direct consequence of the relativity of simultaneity and can be explained in good approximation within the framework of Einstein's special theory of relativity. Using the invariance of the space-time interval, an analytic expression is derived that shows that the time and phase errors increase with increasing along-track distance between the satellites. The predicted errors are in excellent agreement with measurements from TanDEM-X and provide a satisfactory explanation for previously observed digital elevation map (DEM) height offsets that exceeded ±10 m. Consideration of the unexpected relativistic effects is essential for accurate DEM generation in TanDEM-X and has in the meantime been implemented in the operational processing chain. [ABSTRACT FROM AUTHOR]

Given a parametrized family of finite frames, we consider the optimization problem of finding the member of this family whose coefficient space most closely contains a given data vector. This nonlinear least squares problem arises naturally in the context of a certain type of radar system. We derive analytic expressions for the first and second partial derivatives of the objective function in question, permitting this optimization problem to be efficiently solved using Newton's method. We also consider how sensitive the location of this minimizer is to noise in the data vector. We further provide conditions under which one should expect the minimizer of this objective function to be unique. We conclude by discussing a related variational-calculus-based approach for solving this frame optimization problem over an interval of time. [ABSTRACT FROM AUTHOR]

Abstract: A multistatic passive radar system exploits illuminators of opportunity like radio or television transmitters for target surveillance. In this paper we analyze the use of the illumination of television or radio stations broadcasting digital signals (DAB/DVB-T) from a target tracking view point. An important characteristic of this type of illuminators is the joint operation of several illuminators in a single frequency network (SFN). As a consequence it is a priori unknown which measurement belongs to which illuminator. This property expands the typical association task of associating measurements with targets by the task of associating measurements with illuminators. In this paper we present a comprehensive concept for target tracking in DAB/DVB-T networks accounting for the characteristics of this signal. The derived algorithms will be tested with respect to numerical simulations including a sensitivity study for parameter mismatch between simulations and tracking model. [Copyright &y& Elsevier]

The cooperation of an active acoustic source and a large number of distributed passive sensors offers an opportunity for active sonar detection. The system works as follows: first, each sensor compares its matched filter output with a given threshold to obtain a binary local decision—“0” or “1”; then, a fusion center (FC) collects them to make a system-level inference. How effectively to combine these local results—distributed detection fusion—is the concentration of this paper. Suppose that the sensor network is unaware of the target's reflection model. Then, the local detection probabilities cannot be obtained; therefore, the optimal fusion rule is unavailable. The obvious detection strategy is a counting rule test (CRT), which simply counts the total number of 1's and compares it to a threshold. This approach does not require knowledge of sensor locations, and equally considers all network subareas. However, the reflected signal from some targets, such as a submarine, can be highly aspect dependent, and in many instances only sensors in a particular zone can receive its echoes. This paper focuses on the scan statistic, which slides a window across the sensor field, and selects the subarea with the largest number of 1's to make a decision. The scan statistic integrates the aspect-dependence characteristic of the target into detection fusion. With a proper window size, it may suppress the subarea interference, and improve the system-level performance. [ABSTRACT FROM PUBLISHER]

Inverse synthetic aperture radar (ISAR) is one of the radar techniques used to observe 2-D images of a remotely based target using radio waves. If we keep observing the target and consecutively generate multiple ISAR images, which we call an ISAR movie, the target image varies considerably due to the motion of the target. The authors have proposed an algorithm for reconstructing a 3-D target shape from an ISAR movie; however, the algorithm requires a priori knowledge of the relative motion of the target. In this paper, we propose a novel method that estimates the relative motion and the 3-D shape of the target using a multistatic ISAR movie. [ABSTRACT FROM PUBLISHER]

In this paper, we present a new technique to exploit the data acquired simultaneously by multiple radar sensors carried by multiple air platforms to increase the cross-range resolution of inverse synthetic aperture radar (ISAR) images of rotating targets. This distributed ISAR technique is devised for two different cases: 1) multiple-input--multiple-output (MIMO) case with each platform carrying an active radar that transmits and receives RF waveforms and 2) multistatic case with a single platform carrying an active radar (transmitting and receiving) and the remaining platforms equipped with passive sensors (namely, receiving only). The processing chain proposed for the distributed ISAR is shown, together with the results obtained against simulated ISAR data for both the MIMO and the multistatic cases. The performance analysis shows that the proposed technique is able to provide an increase of the cross-range resolution up to the number of platforms in the multistatic case and even higher in the MIMO case, if the platforms are properly located. This is of great benefit in applications where the target rotation angle is insufficient to guarantee the desired resolution. A typical case is the imaging of ship targets with rotation induced by the sea swell structure under low sea state conditions. To make the results appealing for practical application, the performance degradation is also analyzed arising from errors in the knowledge of both the target rotation motion and the acquisition geometry. Experimental data collected by a ground-based radar operating together with a rotating platform are processed by following the presented distributed ISAR technique to validate the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, we consider a multistatic synthetic aperture radar (SAR) imaging scenario where a swarm of airborne antennas, some of which are transmitting, receiving or both, are traversing arbitrary flight trajectories and transmitting arbitrary waveforms without any form of multiplexing. The received signal at each receiving antenna may be interfered by the scattered signal due to multiple transmitters and additive thermal noise at the receiver. In this scenario, standard bistatic SAR image reconstruction algorithms result in artifacts in reconstructed images due to these interferences. In this paper, we use microlocal analysis in a statistical setting to develop a filtered-back projection (FBP) type analytic image formation method that suppresses artifacts due to interference while preserving the location and orientation of edges of the scene in the reconstructed image. Our FBP-type algorithm exploits the second-order statistics of the target and noise to suppress the artifacts due to interference in a mean-square sense. We present numerical simulations to demonstrate the performance of our multistatic SAR image formation algorithm with the FBP-type bistatic SAR image reconstruction algorithm. While we mainly focus on radar applications, our image formation method is also applicable to other problems arising in fields such as acoustic, geophysical and medical imaging. [ABSTRACT FROM AUTHOR]

This paper presents an overview of single-pass interferometric Synthetic Aperture Radar (SAR) missions employing two or more satellites flying in a close formation. The simultaneous reception of the scattered radar echoes from different viewing directions by multiple spatially distributed antennas enables the acquisition of unique Earth observation products for environmental and climate monitoring. After a short introduction to the basic principles and applications of SAR interferometry, designs for the twin satellite missions TanDEM-X and Tandem-L are presented. The primary objective of TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement) is the generation of a global Digital Elevation Model (DEM) with unprecedented accuracy as the basis for a wide range of scientific research as well as for commercial DEM production. This goal is achieved by enhancing the TerraSAR-X mission with a second TerraSAR-X like satellite that will be launched in spring 2010. Both satellites act then as a large single-pass SAR interferometer with the opportunity for flexible baseline selection. Building upon the experience gathered with the TanDEM-X mission design, the fully polarimetric L-band twin satellite formation Tandem-L is proposed. Important objectives of this highly capable interferometric SAR mission are the global acquisition of three-dimensional forest structure and biomass inventories, large-scale measurements of millimetric displacements due to tectonic shifts, and systematic observations of glacier movements. The sophisticated mission concept and the high data-acquisition capacity of Tandem-L will moreover provide a unique data source to systematically observe, analyze, and quantify the dynamics of a wide range of additional processes in the bio-, litho-, hydro-, and cryosphere. By this, Tandem-L will be an essential step to advance our understanding of the Earth system and its intricate dynamics. Enabling technologies and techniques are described in detail. An outlook on future interferometric and tomographic concepts and developments, including multistatic SAR systems with multiple receivers, is provided. [ABSTRACT FROM AUTHOR]

Time-reversal methods have attracted increasing interest recently. The so-called computational time-reversal approach creates an image of the illuminated scene by computing the back-propagated field and is useful for detecting and estimating targets in the scene. In Shi and Nehorai ["Maximum Likelihood Estimation of Point Scatterers for Computational Time-Reversal Imaging," Communications in Information and Systems, vol. 5, no. 2, pp. 227-256, 2005], we estimated point scatterers by maximum-likelihood estimate (MLE) using the Born-approximated physical model, as well as the Foldy-Lax model. In this correspondence, we further find an explicit relationship between energy-based basic time-reversal imaging and the MLE approach: the time-reversal imaging function differs by only a scaling factor from the likelihood imaging function using the estimated scattering potential when a single-scatterer model is employed. Furthermore, this scaling factor is a function of the imaging position only. We show that, as a result, time-reversal imaging has a near-far problem that tends to produce a weaker image for areas further away from the imaging arrays, whereas the MLE-based image is more balanced. Experimental results confirm this conclusion. [ABSTRACT FROM AUTHOR]