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Passive MIMO radar detection in the presence of clutter or multi-path without reference channel

IET radar SONAR AND NAVIGATION 2021年第2期15卷 154-166页

作者： Fazlollahpoor, Mohammad Derakhtian, Mostafa Khorshidi, Shapour Malek Ashtar Univ Technol Fac Marine & Aerial Sci Shiraz Iran Shiraz Univ Dept Elect & Comp Engn Shiraz Iran

Target detection problem in a multiple-input multiple-output (MIMO) radar which includes non-cooperative illuminators of opportunity (IOs) and spatially distributed receivers is discussed. The receivers utilize only one processing channel and discard the difficulties in providing an ideal version of the transmitted waveforms. The signal model, in addition to the receiver noise and the possible echo from the target of interest, considers the direct-path and clutter/multi-path interferences (DPI and MPI). A Rao test and an approximated GLR test detectors are proposed to solve the problem and an innovative recursive algorithm is proposed to simultaneously estimate the nuisance parameters in the test. Then, by regarding some matrix properties in the proposed Rao detector expression, a low complexity version of the Rao detector is proposed. Besides, two detectors based on Rao and GLR principles in the case of active MIMO radar are introduced as the performance upper-bounds for the proposed detectors. The convergence and suitable performance of the proposed detectors are verified by numerical simulations.

关键词： clutter MIMO communication transmitted waveforms spatially distributed receivers receiver noise Rao detector expression possible echo approximated GLR test detectors passive MIMO radar detection MIMO radar ideal version antenna arrays processing channel reference channel multiple-input multiple-output radar radar signal processing target detection problem radar receivers low complexity version object detection innovative recursive algorithm Rao test direct-path passive radar active MIMO radar noncooperative illuminators signal model radar detection

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MIMO radar signal design to improve the MIMO ambiguity function via maximizing its peak

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SIGNAL PROCESSING 2016年 118卷 139-152页

作者： Chitgarha, Mohammad Mandi Radmard, Mojtaba Majd, Mohammad Nazari Karbasi, Seyyed Mohammad Nayebi, Mohammad Mandi Sharif Univ Technol Tehran Iran

One of the important obstacles in MIMO (multiple input multiple output) radars is the issue of designing proper transmit signals. Indeed, the capability of signal design is a significant advantage in MIMO radars, through which, the system can achieve much better performance. Many different aspects of this performance improvement have been considered yet, and the transmit signals have been designed to attain such goal, e.g., getting higher SNR or better detector's performance at the receiver. However, an important tool for evaluating the radar's performance is its ambiguity function. In this paper, we consider the problem of transmit signal design, in order to optimize the ambiguity function of a distributed MIMO radar system via maximizing its peak. (C) 2015 Elsevier B.V. All rights reserved.

关键词： multiple-input multiple-output radar Ambiguity function Waveform design Power allocation Waterfilling

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Cram&x00E9;r-Rao Bounds on Angle Estimating in Bistatic MIMO radar With Non-Orthogonal Waveforms

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IEEE ACCESS 2020年 8卷 62639-62649页

作者： Mao, Chenxing Wang, Ke Shi, Junpeng Wang, Xinhai Yangtze Univ Elect & Informat Sch Jingzhou 434023 Peoples R China Hainan Univ State Key Lab Marine Resource Utilizat South Chin Haikou 570228 Hainan Peoples R China Natl Univ Def Technol Hefei 230037 Anhui Peoples R China Nanjing Marine Radar Inst Nanjing 211153 Jiangsu Peoples R China

Angle estimation is a hot topic in multiple input multiple output (MIMO) radar. However, most of the existing algorithms are only focus on the scenario of ideal orthogonal transmission waveform. In engineering applications, however, non-orthogonal waveforms scenario is more practical. In this paper, we focus on the Cramer-rao bound (CRB) on angle estimation in MIMO radar with non-orthogonal waveforms. Firstly, the angle estimation model in bistatic MIMO radar with non-orthogonal transmit waveforms is given, and the general expression of CRB is deduced. Thereafter, the CRBs in some special cases are discussed, e.g., monostatic geometry, orthogonal transmit waveforms scenario. In addition, theoretical comparisons between the stochastic CRBs and the deterministic ones are presented. Finally, the computer simulations are carried out to verify the theoretically ones.

关键词： MIMO radar radar antennas Estimation Covariance matrices Receiving antennas Transmitting antennas multiple-input multiple-output radar non-orthogonal transmit waveforms Cramer-Rao bound

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Nuclear norm minimization framework for DOA estimation in MIMO radar

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SIGNAL PROCESSING 2017年 135卷 147-152页

作者： Wang, Xianpeng Wang, Luyun Li, Xiumei Bi, Guoan Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Hainan Univ State Key Lab Marine Resource Utilizat South Chin Hainan 570228 Peoples R China Hainan Univ Coll Informat Sci & Technol Hainan 570228 Peoples R China Dalian Univ Technol City Coll Sch EEA Dalian Peoples R China Hangzhou Normal Univ Sch ISE Hangzhou Zhejiang Peoples R China

In this paper, the direction of arrival (DOA) estimation for noncircular sources in multiple-input multiple output (MIMO) radar is dealt with by a novel nuclear norm minimization (NNM) framework. The proposed method exploits the noncircular property of signals to extend the data model for doubling the array aperture. Then a block sparse model of the extended data is formulated without the influence of the unknown noncircularity phase, and a novel signal reconstruction algorithm based on nuclear norm minimization is proposed to recover the block-sparse matrix. In addition, a weight matrix based on the reduced dimensional noncircular Capon (RD NC-Capon) spectrum is designed to reweight the nuclear norm minimization for enhancing the sparsity of solution. Finally, the DOA is estimated from the non-zero blocks of the reconstructed matrix. Due to exploiting the extended array aperture and block-sparse information, the proposed method provides superior DOA estimation performance and higher angular resolution. Furthermore, the proposed method has a low sensitivity to the priori information on the number of sources. Simulation results are presented to verify the effectiveness and advantages of the proposed method.

关键词： multiple-input multiple-output radar Direction of arrival estimation Sparse representation Noncircular signal Nuclear norm minimization

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A sparse direction-of-arrival estimation algorithm for MIMO radar in the presence of gain-phase errors

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DIGITAL SIGNAL PROCESSING 2017年 69卷 193-203页

作者： Liu, Jing Zhou, Weidong Wang, Xianpeng Huang, Defeng (David) Harbin Engn Univ Coll Automat Harbin 150001 Heilongjiang Peoples R China Univ Western Australia Sch Elect Elect & Comp Engn Nedlands WA Australia Hainan Univ Coll Informat Sci & Technol Haikou 570228 Hainan Peoples R China

In this paper, the problem of direction-of-arrival (DOA) estimation for monostatic multiple-input multiple-output (MIMO) radar with gain-phase errors is addressed, by using a sparse DOA estimation algorithm with fourth-order cumulants (FOC) based error matrix estimation. Useful cumulants are designed and extracted to estimate the gain and the phase errors in the transmit array and the receive array, thus a reliable error matrix is obtained. Then the proposed algorithm reduces the gain-phase error matrix to a low dimensional one. Finally, with the updated gain-phase error matrix, the FOC-based reweighted sparse representation framework is introduced to achieve accurate DOA estimation. Thanks to the fourth-order cumulants based gain-phase error matrix estimation, and the reweighted sparse representation framework, the proposed algorithm performs well for both white and colored Gaussian noises, and provides higher angular resolution and better angle estimation performance than reduced-dimension MUSIC (RD-MUSIC), adaptive sparse representation (adaptive-SR) and ESPRIT-based algorithms. Simulation results verify the effectiveness and advantages of the proposed method. (C) 2017 Elsevier Inc. All rights reserved.

关键词： multiple-input multiple-output radar Direction-of-arrival estimation Gain-phase errors Fourth-order cumulants Sparse representation

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Target Localization and Clock Refinement in Distributed MIMO radar Systems With Time Synchronization Errors

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2021年 69卷 3088-3103页

作者： Song, Haibo Wen, Gongjian Liang, Yuanyuan Zhu, Lingxiao Luo, Dengsanlang Natl Univ Def Technol Coll Elect Sci Natl Key Lab Sci & Technol ATR Changsha 410073 Peoples R China

Achieving accurate clock synchronization may not be feasible for distributed multiple-input multiple-output (MIMO) radar systems with non-ideal clocks of the sensors. In this paper, the problem of target localization and clock synchronization in distributed MIMO radar systems in presence of time synchronization errors is addressed by utilizing time delay measurements. Firstly, the necessity to consider time synchronization errors when locating a target is illustrated by analyzing the increase in Cramer-Rao lower bound (CRLB) of the target position due to the time synchronization error. Then, a self-synchronized localization framework based on the hybrid maximum likelihood and maximum a posteriori estimator is proposed to estimate the target position and time synchronization error sequentially. Specifically, a method based on the levenberg marquardt algorithm and an analytical solution are developed respectively to estimate the target position, and a combination strategy is recommended further based on the two methods to achieve a more accurate target position estimate. The time synchronization error is figured out then by utilizing the target position estimate. Meanwhile, the closed-form solution of estimating the target position and time synchronization error is analytically proved to be approximately unbiased and can attain the CRLB under weak noise conditions. It is demonstrated through numerical simulations that the combination strategy has better estimation performance than the two methods. Simultaneously, simulation results show that the proposed self-synchronized localization method outperforms the state-of-the-art algorithms in the target position and time synchronization error estimation accuracy.

关键词： Target localization clock synchronization time delay multiple-input multiple-output radar

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Decomposition Optimization Algorithms for Distributed radar Systems

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2016年第24期64卷 6443-6458页

作者： Ma, Ying Chen, Sheng Xing, Chengwen Bu, Xiangyuan Hanzo, Lajos Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England King Abdulaziz Univ Jeddah 21589 Saudi Arabia

Distributed radar systems are capable of enhancing the detection performance by using multiple widely spaced distributed antennas. With prior statistic information of targets, resource allocation is of critical importance for further improving the system's achievable performance. In this paper, the total transmitted power is minimized at a given mean-square target-estimation error. We derive two iterative decomposition algorithms for solving this nonconvex constrained optimization problem, namely, the optimality condition decomposition (OCD)-based and the alternating direction method of multipliers (ADMM)-based algorithms. Both the convergence performance and the computational complexity of our algorithms are analyzed theoretically, which are then confirmed by our simulation results. The OCD method imposes a much lower computational burden per iteration, while the ADMM method exhibits a higher per-iteration complexity, but as a benefit of its significantly faster convergence speed, it requires less iterations. Therefore, the ADMM imposes a lower total complexity than the OCD. The results also show that both of our schemes outperform the state-of-the-art benchmark scheme for the multiple-target case, in terms of the total power allocated, at the cost of some degradation in localization accuracy. For the single-target case, all the three algorithms achieve similar performance. Our ADMM algorithm has similar total computational complexity per iteration and convergence speed to those of the benchmark.

关键词： Alternating direction method of multipliers localization multiple-input multiple-output radar optimality condition decomposition resource allocation

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An Approximately Efficient Estimator for Moving Target Localization in Distributed MIMO radar Systems in Presence of Sensor Location Errors

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IEEE SENSORS JOURNAL 2020年第2期20卷 931-938页

作者： Song, Haibo Wen, Gongjian Zhu, Lingxiao Natl Univ Def Technol Coll Elect Sci Natl Key Lab Sci & Technol ATR Changsha 410073 Peoples R China

In this paper, a novel algebraic closed-form method is proposed to estimate the position and velocity of a moving target in distributed multiple-input multiple-output radar systems with erroneous sensor locations by utilizing time delay and Doppler shift measurements. Unlike the existing methods that introduce nuisance parameters to build the pseudo-linear equations, the proposed method uses the singular value decomposition approach to establish new linear equations with regard to the target location with no nuisance parameters, and then derives a weighted least-squares (WLS) solution. To further improve the localization accuracy, the solution is refined through estimating the error by another WLS estimator. Based on the theoretical derivation and numerical simulations, the proposed estimator is demonstrated to be approximately unbiased and can attain the CRLB under small noise conditions. Moreover, the simulation results show that the proposed method achieves better target location accuracy than the state-of-the-art algorithms.

关键词： Target localization sensor location error Doppler shift time delay multiple-input multiple-output radar

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Joint transmit-receive B-PARAFAC method for angle estimation in bistatic MIMO radar

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DIGITAL SIGNAL PROCESSING 2019年 92卷 54-61页

作者： Xu, Baoqing Zhao, Yongbo Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China Xidian Univ Collaborat Innovat Ctr Informat Sensing & Underst Xian 710071 Shaanxi Peoples R China

In this paper, a joint transmit-receive beamspace parallel factor (B-PARAFAC) method is proposed for angle estimation in bistatic MIMO radar. Combining with the forward-backward averaging technique, the beamspace transformation technique is firstly extended to the tensor case, which utilizes the multidimensional structure of the received data. Specially, the transmit beamspace (TB) and receive beamspace (RB) matrices are obtained through convex optimization, whose matrix structure can be properly designed to construct a real-valued tensor model. Furthermore, different from the traditional discrete Fourier transform (DFT) beamspace filters, the bandwidth and sidelobe level of the proposed beamspace filters can be flexibly controlled as required, which can greatly improve the mainlobe-to-sidelobe ratio (MSR). We prove that the constructed real-valued tensor after beamspace transformation still follows a PARAFAC model. Compared with the unitary PARAFAC (U-PARAFAC) method, the proposed B-PARAFAC method has more attractive performance especially in low signal-to-noise ratio (SNR) and requires less computation. Simulation results demonstrate the effectiveness of the proposed method. (C) 2019 Elsevier Inc. All rights reserved.

关键词： multiple-input multiple-output radar Tensor decomposition Beamspace transformation Angle estimation

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Computationally efficient DOD and DOA estimation for bistatic MIMO radar with propagator method

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INTERNATIONAL JOURNAL OF ELECTRONICS 2012年第9期99卷 1207-1221页

作者： Zhang, Xiaofei Wu, Hailang Li, Jianfeng Xu, Dazhuan Nanjing Univ Aeronaut & Astronaut Dept Elect Engn Nanjing 210016 Peoples R China

In this article, we consider a computationally efficient direction of departure and direction of arrival estimation problem for a bistatic multiple-input multiple-output (MIMO) radar. The computational loads of the propagator method (PM) can be significantly smaller since the PM does not require any eigenvalue decomposition of the cross correlation matrix and singular value decomposition of the received data. An improved PM algorithm is proposed to obtain automatically paired transmit and receive angle estimations in the MIMO radar. The proposed algorithm has very close angle estimation performance to conventional PM, which has a much higher complexity than our algorithm. For high signal-to-noise ratio, the proposed algorithm has very close angle estimation to estimation of signal parameters via rotational invariance technique algorithm. The variance of the estimation error and Cramer-Rao bound of angle estimation are derived. Simulation results verify the usefulness of our algorithm.

关键词： angle estimation multiple-input multiple-output radar propagator method

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