Search

• CFAR property in Weibull-distributed clutter was maintained and effective in controlled scenario. • Good detection performance in the presence of interfering targets with a large ICR. • Modelling and simulation of sea clutter via mixed Weibull distribution. In maritime surveillance, sea clutter represents a major obstacle to target detection accuracy due to missed or false alarms. Several methods have been proposed to find the most efficient. However, most of these methods have only been tested with simulated data, and their applicability and success in a real environment cannot be guaranteed. This work proposes constant false alarm rate (CFAR) detection techniques tailored to mixed Weibull-distributed sea clutter. The mixed Weibull distribution was used to model a mixture of Gaussian and non-Gaussian data. For CFAR detection in mixed Weibull distribution and Weibull clutter, the log t CFAR (logt-CFAR), Weber Haykin CFAR (WH CFAR), Geometric Mean Order Statistic CFAR (GMOS-CFAR), Trimmed Mean Order Statistic CFAR (TMOS-CFAR), Inclusion/Exclusion CFAR (IE-CFAR), and Weber Haykin Order Statistic CFAR (WHOS-CFAR) algorithms were performed. Both synthetic and actual ice multi-parameter imaging X-band (IPIX) radar data were used for experimental verification of this distribution. Simulation studies demonstrated that the proposed detectors maintain the CFAR property in Weibull-distributed clutter, making them effective in controlled scenarios, and confirming how better is the detection performance compared to other detection methods. This research bridges a critical gap in radar signal processing by significantly improving the detection of targets in challenging clutter environments. [ABSTRACT FROM AUTHOR]

Compared with the traditional pulse repetition interval (PRI) parameters, PRI pattern can describe the temporal characteristics of radar more completely, and the method based on PRI pattern is more suitable for tasks of deinterleaving and identification. Therefore, effective reconstruction of PRI pattern is an important task in radar signal processing. However, previous PRI pattern reconstruction methods either set too many subjective parameters or have high requirements for the number of pulses, making it not very practical for analyzing actual radar signals. In this paper, the temporal rule of pulse train is modeled from the perspective of radar timing state switching. Then the pulses of different timing states in the pulse train are clustered based on state merging algorithms in model learning. The transitions between different timing states are established based on the pulse sets obtained by clustering. Finally, the PRI pattern of radar is reconstructed after processing interferential pulses and missing pulses. Based on the above method, this paper further proposes a method to reconstruct PRI patterns of all radars in interleaved pulse trains. Simulation results verify the effectiveness of the proposed PRI pattern reconstruction method. • PRI pattern reconstruction framework based on model learning. • Pulse clustering algorithm based on state merging. • Radar emitter division method for interleaved pulse trains. • Better adaptability to the data noises, PRI pattern order and small pulse number. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of robust Stackelberg game-based power control (RSG-PC) for spectral coexisting multistatic radar and massive multiple-input multiple-output (MIMO) communication systems. Recognizing that the path propagation gains cannot be assumed to be constant, the column-wise model is employed to describe the uncertainty of the parameters. The primary objective of the RSG-PC scheme is to minimize the worst-case radiated power of each radar with uncertain path gains for a specified signal-to-interference-plus-noise ratio (SINR) requirement for target detection, while the massive MIMO communication base station (MIMO-CBS) is protected from the interference of radar transmissions. The hierarchical competition between the massive MIMO-CBS and multiple radars are modeled as a robust single-leader multi-follower Stackelberg game. In the considered game model, the massive MIMO-CBS plays as the leader to decide the prices first through the maximization of its own utility. The radars act as the followers, who compete with each other in a non-cooperative Nash game according to the released interference prices from the massive MIMO-CBS subsequently. Based on the theoretical findings on the existence and uniqueness of the robust Nash equilibrium (RNE) in the formulated game, we present an iterative power control approach that guarantees the convergence to the RNE. Finally, the numerical simulations are provided to verify that our RSG-PC scheme can provide efficient power resource utilization, guarantee a predefined target detection performance, and also protect the quality of service (QoS) of massive MIMO-CBS with uncertainties in path propagation gains. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the detection performance of non-coherent radar for correlated gamma fluctuating targets in K distributed sea clutter. We present the radar signal models at first. Then we derive the mathematical expression of the radar detection probability. We verify the correctness of the theoretical derivations by Monte Carlo simulations. We further analyze the radar detection performances in various clutter and target circumstances. [ABSTRACT FROM AUTHOR]

Target detection in clutter is a fundamental problem in radar signal processing. When the received radar signal contains only few pulses, it is difficult to achieve a satisfactory performance using the traditional detection algorithm. In recent times, a generalized constant false alarm rate (CFAR) detector on the Riemannian manifold of Hermitian positive-definite (HPD) matrix was proposed. The employment of this detector, which compares the Riemannian distance between the covariance matrix of the cell under test (CUT) and an average matrix of reference cells with a given threshold, has significantly improved the detection performance. However, the application of this detector in real scenarios is still limited by two problems; it is computationally expensive and the detection performance is not very good since the Riemannian distance is utilized. In this paper, the symmetrized Kullback–Leibler (sKL) and the total Kullback–Leibler (tKL) divergences, instead of the Riemannian distance, are used as dissimilarity measures in the matrix CFAR detector. According to sKL and tKL divergences, three average matrices, the sKL mean, the sKL median, and the tKL t center, are derived. Furthermore, the relationship between the detection performance and the anisotropy of the distance measure used in the matrix CFAR detector is explored. Numerical experiments and real radar sea clutter data are given to confirm the superiority of the proposed algorithms in terms of the computational complexity and the detection performance. [ABSTRACT FROM AUTHOR]

Frequency diversity array (FDA) radar can continuously scan the whole airspace within a pulse duration by introducing a stepping frequency increment among each array element. The integrated radar-communication system (IRCS) based on FDA can perform multi-directional communication and target detection in a single pulse. We propose the waveform design and signal processing methods for IRCS based on FDA. Firstly, the transmit signal model adopts the pulse mode, and each pulse is divided into multiple sub-pulses. The communication symbols are embedded into the radar transmit waveform of each sub-pulse through phase-shift keying. Then, the tangent frequency-modulated signal is employed as the baseband waveform with the space coding by the Zadoff-Chu sequence to ensure pulse compression performance. Finally, the signal processing methods of radar and communication are proposed, respectively. The performances are verified in terms of the transmit-receive beampattern, multi-dimensional ambiguity function, and bit error rate. The simulation results demonstrate that the proposed method can perform multi-symbol communication under the premise of satisfying the directional scanning and pulse compression performances. [ABSTRACT FROM AUTHOR]

This study explored a novel method based on eigenvalue decomposition (EVD) and independent component analysis (ICA) to separate the multi-component radar signal in the single channel. By exploiting the generalized periodicity of the radar signal, the proposed method structures the multi-dimensional matrix from the observed signal in single-channel through EVD, then applies ICA to the matrix to determine the basic waveform of each component, and finally reconstructs the component signals. Simulation results confirmed the effectiveness of the proposed method and compared it with other methods, although the performance of proposed approach is a bit worse than some other method when processing radar signals, the most outstanding advantage of the proposed approach is that it does not require any other known conditions, and it can recover the component signals with a satisfactory level, so it can yet be regarded as an effective method. [ABSTRACT FROM AUTHOR]

The challenge of current radiocommunication systems is the efficient use of the frequency spectrum. One of the rapidly evolving tools is a RadCom system, which combines the functionality of a radar sensor with a communication interface. RadCom systems are used in several fields, and the presented work is focused on their applications in the automotive industry. The goal was to design a modulation technique and generate modulation data, which will be suitable for radar determination of the distance and velocity of targets, but also enable their mutual communication. A model of the RadCom system, which simultaneously allows a simulation of detection and communication of several moving targets, has been developed. Herein, a method of generating pseudo-random data based on the MD5 hashing algorithm is described. The proposed method of radar signal processing enables unambiguous detection of moving targets and determination of the position and velocity of these targets. Principles of synchronization and coding of a radar and communication mode of the RadCom system are explained. A numerical verification of the proposed algorithms using simulation tools is discussed in the final part of the work. The proposed system solution achieves more than 70% probability that the decoded message will not contain erroneous bits. [ABSTRACT FROM AUTHOR]

Principal Component Analysis (PCA) is a simple non-parametric method for extracting relevant information from high-dimensional data sets. In this paper, we analyze the data collected from the Indian MST (Mesosphere, Stratosphere, Troposphere) radar at Gadanki (13.5°N, 79.2°E) using PCA. We tested the PCA for various simulated signals like narrowband, wideband and exponential signals which may contain more than one frequency both in absence and presence of noise. For the simulated data, it is observed that PCA works for low SNR, i.e. it successfully detects the frequency in the highly noise-corrupted signal also. Finally, we applied PCA to the radar data for estimating the power spectrum and thus in turn estimating the Doppler frequency components. We estimate the zonal (U), meridional (V), wind speed (W) etc. from the Doppler frequencies. Compared with existing algorithms, PCA works well at higher altitudes and results have been validated using the GPS sonde data. [ABSTRACT FROM AUTHOR]

Abstract: Autonomous wireless sensor networks consisting of different types of sensor modalities have been receiving greater attention from researchers due to their versatility and portability. These autonomous sensor networks commonly include passive sensors such as infrared, acoustic, vibration, and magnetic nodes. However, fusion of active sensors in the integrated sensor network, such as Doppler radars, may offer powerful capabilities for many different sensing and classification tasks. In this work, we demonstrate the design and implementation of an autonomous wireless sensor network integrating a Doppler sensor with commercial off-the-shelf components. We investigate the effect of various types of target materials on the measured radar signal as one of the applications of the newly designed radar–mote network. Different types of materials affect the amount of energy reflected back to the source of an electromagnetic wave. We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets. We validate our simulation results using real experimental data collected through our autonomous radar–mote sensor network using various types of targets. [Copyright &y& Elsevier]

Abstract: This work deals with the spectrum parameters estimation of a weather radar signal, namely velocity, variance and spectrum width. A new tool – based on the Ramanujan sums, , which come from the arithmetic functions of the number theory – has been introduced in signal processing. As compared to pulse pair and Fourier algorithms, new results have been obtained by the use of the Ramanujan-Fourier Transform (RFT) for the Doppler spectrum estimation of a real weather data provided by terminal pulse Doppler radar (WSR-88D). [Copyright &y& Elsevier]

Multiple-snapshot maximum-likelihood (ML) direction of arrival (DOA) estimation problem is studied for the intermittent jamming scenario. The intermittent jamming modality is based on the assumption that only a subset of the collected snapshots are contaminated by the jammer while the others are jammer-free; but the receiver does not know which is which. This type of jamming is frequently encountered in practice either inadvertently, say due to the sporadic activity of a non-hostile system; or intentionally, say due to the activity of an adversary sweeping the operational bandwidth of the receiver. Exact maximum likelihood solution for the problem is analytically intractable and an expectation maximization (EM) method based solution is developed for coherent and non-coherent signal models. Coherent signal model assumes that the phase difference between the coefficients of two consecutive snapshots are known a-priori which is an assumption compatible with the Swerling-1/3 target models in the radar signal processing literature. Non-coherent signal model does not have such an assumption and it is suitable for Swerling-2/4 targets. The suggested EM based solution is shown to yield an important estimation accuracy improvement over conventional maximum-likelihood solution which ignores the intermittency of jammer and also over the atomic norm based high resolution estimation techniques. Cramer-Rao type performance lower bounds for the problem is also provided to illustrate the efficacy of the suggested estimator. [ABSTRACT FROM AUTHOR]

This paper deals with the covariance estimation and its application in radar signal processing when the number of the secondary data is limited. We model the covariance estimation as a color loading version and use three different geometric means to derive three kinds of knowledge-aided (KA) covariance estimators, namely, KA Euclid (KA-E) metric estimator, KA Power-Euclid (KA-PE) metric estimator, and KA Log-Euclid (KA-LogE) metric estimator. Experimental results on simulation and measured data demonstrate that the proposed estimators achieve better performance than their natural competitors and keep good constant false alarm ratio (CFAR) property. Among the three proposed estimators, the KA-E estimator has the best performance. [ABSTRACT FROM AUTHOR]

In this paper, a novel design and processing of nearly orthogonal waveforms based on frequency modulated continuous wave (FMCW) signals for multiple-input, multiple-output (MIMO) radars is presented. The design, implementation and results of the complete system, capable of detection and imaging of radar targets, are here described. The orthogonality of sounding signals is critical for multi-channel radar applications since the interference between signals can significantly limit the radar's ability for observation of weak targets in presence of stronger targets and background clutter. The orthogonal waveforms are designed by coding consecutive complex FMCW signals in a frame so that they can be sent to the different transmit antennas of the radar allowing the simultaneous operation of all transmit channels. Unlike time division switching approaches, the orthogonality in the proposed architecture, is achieved by applying several coding techniques, at a symbol level: Golay complementary, Zadoff Chu, Direct Spread Spectrum (DSS), Space-Time Block Coded, Discrete Fourier Transform (DFT) and Costas based sequences. Moreover, a radar receiver processing, based on a complex frame based convolution between transmit and received waveforms together with 4-dimensional Fast Fourier Transform (4D-FFT) beamforming, is presented. This allows for a fast and complete sensing of range, azimuth, elevation and Doppler in a single frame. The performance of the proposed waveforms is evaluated through the analysis of their cross ambiguity functions and imaging capabilities, while the general performance of the radar's receiver processing is shown through the use of multiple radar images. The flexibility in generating such orthogonal coded waveforms and the proposed general receiver architecture are an important first step for developing a future software programmable MIMO radar. [ABSTRACT FROM AUTHOR]