scholarly journals Target Localization Methods Based on Iterative Super-Resolution for Bistatic MIMO Radar

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 341
Author(s):  
Jianhe Du ◽  
Meng Han ◽  
Libiao Jin ◽  
Yan Hua ◽  
Shufeng Li

The direction-of-departure (DOD) and the direction-of-arrival (DOA) are important localization parameters in bistatic MIMO radar. In this paper, we are interested in DOD/DOA estimation of both single-pulse and multiple-pulse multiple-input multiple-output (MIMO) radars. An iterative super-resolution target localization method is firstly proposed for single-pulse bistatic MIMO radar. During the iterative process, the estimated DOD and DOA can be moved from initial angles to their true values with high probability, and thus can achieve super-resolution estimation. It works well even if the number of targets is unknown. We then extend the proposed method to multiple-pulse configuration to estimate target numbers and localize targets. Compared with existing methods, both of our proposed algorithms have a higher localization accuracy and a more stable performance. Moreover, the proposed algorithms work well even with low sampling numbers and unknown target numbers. Simulation results demonstrate the effectiveness of the proposed methods.

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2788 ◽  
Author(s):  
Yuehao Guo ◽  
Xianpeng Wang ◽  
Wensi Wang ◽  
Mengxing Huang ◽  
Chong Shen ◽  
...  

In the paper, the estimation of joint direction-of-departure (DOD) and direction-of-arrival (DOA) for strictly noncircular targets in multiple-input multiple-output (MIMO) radar with unknown mutual coupling is considered, and a tensor-based angle estimation method is proposed. In the proposed method, making use of the banded symmetric Toeplitz structure of the mutual coupling matrix, the influence of the unknown mutual coupling is removed in the tensor domain. Then, a special enhancement tensor is formulated to capture both the noncircularity and inherent multidimensional structure of strictly noncircular signals. After that, the higher-order singular value decomposition (HOSVD) technology is applied for estimating the tensor-based signal subspace. Finally, the direction-of-departure (DOD) and direction-of-arrival (DOA) estimation is obtained by utilizing the rotational invariance technique. Due to the use of both noncircularity and multidimensional structure of the detected signal, the algorithm in this paper has better angle estimation performance than other subspace-based algorithms. The experiment results verify that the method proposed has better angle estimation performance.


2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Idnin Pasya ◽  
Naohiko Iwakiri ◽  
Takehiko Kobayashi

This paper presents a joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation in a multiple-input multiple-output (MIMO) radar utilizing ultra wideband (UWB) signals in detecting targets with fluctuating radar cross sections (RCS). The UWB MIMO radar utilized a combination of two-way MUSIC and majority decision based on angle histograms of estimated DODs and DOAs at each frequency of the UWB signal. The proposed angle estimation scheme was demonstrated to be effective in detecting targets with fluctuating RCS, compared to conventional spectra averaging method used in subband angle estimations. It was found that a wider bandwidth resulted in improved estimation performance. Numerical simulations along with experimental evaluations in a radio anechoic chamber are presented.


2014 ◽  
Vol 513-517 ◽  
pp. 3029-3033 ◽  
Author(s):  
Jian Feng Li ◽  
Wei Yang Chen ◽  
Xiao Fei Zhang

In this paper, joint direction of departure (DOD) and direction of arrival (DOA) estimation for multiple-input multiple-output (MIMO) radar with unknown mutual coupling is studied. An improved propagator calculation method is proposed to overcome the performance degradation problem when signal to noise ratio (SNR) is low. Thereafter, according to the Toeplitz structure of the mutual coupling matrix, the rotational invariance can be extracted for the angle estimation regardless of the mutual coupling from the augmented propagator matrix. The angle estimation performance of the proposed algorithm is better than that of estimation of signal parameters via rotational invariance techniques (ESPRIT)-like algorithm and conventional PM-like method, and angles are automatically paired. The simulation results verify the effectiveness of the algorithm.


Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2177
Author(s):  
Jiaxiong Fang ◽  
Yonghong Liu ◽  
Yifang Jiang ◽  
Yang Lu ◽  
Zehao Zhang ◽  
...  

In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Dang Xiaofang ◽  
Chen Baixiao ◽  
Yang Minglei ◽  
Zheng Guimei

The beamspace unitary ESPRIT (B-UESPRIT) algorithm for estimating the joint direction of arrival (DOA) and the direction of departure (DOD) in bistatic multiple-input multiple-output (MIMO) radar is proposed. The conjugate centrosymmetrized DFT matrix is utilized to retain the rotational invariance structure in the beamspace transformation for both the receiving array and the transmitting array. Then the real-valued unitary ESPRIT algorithm is used to estimate DODs and DOAs which have been paired automatically. The proposed algorithm does not require peak searching, presents low complexity, and provides a significant better performance compared to some existing methods, such as the element-space ESPRIT (E-ESPRIT) algorithm and the beamspace ESPRIT (B-ESPRIT) algorithm for bistatic MIMO radar. Simulation results are conducted to show these conclusions.


2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lin Li ◽  
Fangfang Chen ◽  
Jisheng Dai

A novel MUSIC-type algorithm is derived in this paper for the direction of departure (DOD) and direction of arrival (DOA) estimation in a bistatic MIMO radar. Through rearranging the received signal matrix, we illustrate that the DOD and the DOA can be separately estimated. Compared with conventional MUSIC-type algorithms, the proposed separate MUSIC algorithm can avoid the interference between DOD and DOA estimations effectively. Therefore, it is expected to give a better angle estimation performance and have a much lower computational complexity. Meanwhile, we demonstrate that our method is also effective for coherent targets in MIMO radar. Simulation results verify the efficiency of the proposed method, particularly when the signal-to-noise ratio (SNR) is low and/or the number of snapshots is small.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jinli Chen ◽  
Jiaqiang Li ◽  
Peng Li ◽  
Yanping Zhu ◽  
Weijun Long

In bistatic multiple-input multiple-output (MIMO) radar, range migration and invalidly synthesized virtual array resulting from the serious mismatch of matched filter make it difficult to estimate direction of departure (DOD) and direction of arrival (DOA) of high speed target using the traditional superresolution algorithms. In this study, a method for joint DOD and DOA estimation of high speed target using bistatic MIMO radar is proposed. After multiplying the received signals with the conjugate of the delayed versions of the transmitted signals, Fourier transform (FT) of the multiplied signals over both fast time and slow time is employed. Then, the target components of radar return corresponding to the different transmitted waveforms can be perfectly separated at the receivers by extracting the target frequency-domain data along slow-time frequency dimension when the delay between the transmitted signals and their subsequent returns is timed. By splicing the separated target components distributed along several range cells, the virtual array can be formed, and then DOD and DOA of high speed target can be estimated using the superresolution algorithm with the range migration and the mismatch of matched filter properly removed. Simulation results have proved the validity of the proposed algorithm.


2013 ◽  
Vol 694-697 ◽  
pp. 2550-2556 ◽  
Author(s):  
Ding Jie Xu ◽  
Mo Xuan Li ◽  
Xian Peng Wang

An improved algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation in bistatic MIMO radar based on fourth order cumulants is presented. Firstly, the data of receiver is reset and divided to acquire the rotational invariance property of transmitter and receiver, respectively. The fourth order cumulants matrixes in twain are constructed which are based on the basic definition of the cumulant. Then we use the propagator method (PM), which only requires linear operation but does not involve any eigendecomposition of the cumulant matrix, to estimate the DODs and DOAs, respectively. Finally, the maximum likelihood method is used to solve the pairing problem. The proposed method is effective in prohibiting the Gaussian colored noise and improves the performance of the angle estimation slightly. It does not need two-dimensional spectrum peak searching and eigenvalue decomposition on the cumulant matrix, thus the computation complexity is reduced. At the same time, it has no exceptive claim on the number of receive arrays or receive arrays. Simulation results verify the effectiveness and feasibility of the proposed method.


2014 ◽  
Vol 23 (08) ◽  
pp. 1450106 ◽  
Author(s):  
WEIYANG CHEN ◽  
XIAOFEI ZHANG

This paper investigates the problem of angle estimation for bistatic multiple-input multiple-output (MIMO) radar with non-uniform linear arrays, and proposes an improved spectrum searching generalized estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm for joint direction of departure (DOD) and direction of arrival (DOA) estimation algorithm in bistatic MIMO radar. The proposed algorithm obtains initial estimation of angles obtained from the signal subspace, and uses the 1D local searchings to achieve the joint estimation of DOD and DOA. Compared to the spectrum searching generalized-ESPRIT algorithm which requires the global searchings and additional pairing, the proposed algorithm just needs the local searchings and obtains automatically paired 2D angle estimation. The angle estimation performance of the proposed algorithm is almost the same as that of the generalized-ESPRIT algorithm, and better than ESPRIT-like algorithm. Furthermore, the proposed algorithm is suitable for irregular array geometry, has much lower complexity than the spectrum searching generalized-ESPRIT algorithm, and imposes less constraint on the transmit/receive sensor spacing, which need not be limited to a half-wavelength strictly. The simulation results verify the effectiveness of the algorithm.


2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Junxiang Wang ◽  
Ping Huang ◽  
Dingjie Xu

A joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation algorithm based on tensor subspace approach for partially calibrated bistatic multiple-input multiple-output (MIMO) radar is proposed. By exploiting the multidimensional structure of the received data, a third-order measurement tensor is constructed. Consequently, the tensor-based signal subspace is achieved using the higher-order singular value decomposition (HOSVD). To achieve accurate DOA estimation with partially calibrated array, a closed-form solution is provided to estimate the gain-phase uncertainties of the transmit and receive arrays by modeling the imperfections of the arrays. Simulation results demonstrate the effectiveness of the proposed calibration algorithm.


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