Phased-MIMO Radar in Low SNR Regime

2019 ◽  
pp. 357-362
Author(s):  
Samarendra Nath Sur ◽  
Rabindranath Bera ◽  
Bansibadan Maji
Keyword(s):  
Mimo Radar ◽  
Low Snr

Adaptive Sparse Recovery of Moving Targets for Distributed MIMO Radar

2014 ◽  
Vol 933 ◽  
pp. 450-455
Author(s):  
Hui Yu ◽  
Guang Hua Lu ◽  
Hai Long Zhang
Keyword(s):  
High Resolution ◽  
Sparse Recovery ◽  
Mimo Radar ◽  
Moving Target ◽  
Recovery Algorithm ◽  
Low Snr ◽  
Computation Efficiency ◽  
Target Imaging ◽  
Moving Target Imaging ◽  
Recovery Error

The high resolution and better recovery performance with distributed MIMO radar would be significantly degraded when the target moves at an unknown velocity. In this paper, we propose an adaptive sparse recovery algorithm for moving target imaging to estimate the velocity and image jointly with high computation efficiency. With an iteration mechanism, the proposed method updates the image and estimates the velocity alternately by sequentially minimizing the norm and the recovery error. Numerical simulations are carried out to demonstrate that the proposed algorithm can retrieve high-resolution image and accurate velocity simultaneously even in low SNR.

scholarly journals Guaranteed Stability of Sparse Recovery in Distributed Compressive Sensing MIMO Radar

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yu Tao ◽  
Gong Zhang ◽  
Jindong Zhang
Keyword(s):  
Compressive Sensing ◽  
Matching Pursuit ◽  
Mimo Radar ◽  
Radar System ◽  
Sensing Matrix ◽  
Joint Measurement ◽  
Low Snr ◽  
The Face ◽  
Distributed Compressive Sensing ◽  
Average Coherence

Low SNR condition has been a big challenge in the face of distributed compressive sensing MIMO radar (DCS-MIMO radar) and noise in measurements would decrease performance of radar system. In this paper, we first devise the scheme of DCS-MIMO radar including the joint sparse basis and the joint measurement matrix. Joint orthogonal matching pursuit (JOMP) algorithm is proposed to recover sparse targets scene. We then derive a recovery stability guarantee by employing the average coherence of the sensing matrix, further reducing the least amount of measurements which are necessary for stable recovery of the sparse scene in the presence of noise. Numerical results show that this scheme of DCS-MIMO radar could estimate targets’ parameters accurately and demonstrate that the proposed stability guarantee could further reduce the amount of data to be transferred and processed. We also show the phase transitions diagram of the DCS-MIMO radar system in simulations, pointing out the problem to be further solved in our future work.

scholarly journals Subspace Compressive GLRT Detector for MIMO Radar in the Presence of Clutter

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Siva Karteek Bolisetti ◽  
Mohammad Patwary ◽  
Khawza Ahmed ◽  
Abdel-Hamid Soliman ◽  
Mohamed Abdel-Maguid
Keyword(s):  
Mathematical Model ◽  
Computational Complexity ◽  
Performance Analysis ◽  
False Alarm ◽  
Target Detection ◽  
Mimo Radar ◽  
Detection Performance ◽  
Radar Target ◽  
Significant Deterioration ◽  
Low Snr

The problem of optimising the target detection performance of MIMO radar in the presence of clutter is considered. The increased false alarm rate which is a consequence of the presence of clutter returns is known to seriously degrade the target detection performance of the radar target detector, especially under low SNR conditions. In this paper, a mathematical model is proposed to optimise the target detection performance of a MIMO radar detector in the presence of clutter. The number of samples that are required to be processed by a radar target detector regulates the amount of processing burden while achieving a given detection reliability. While Subspace Compressive GLRT (SSC-GLRT) detector is known to give optimised radar target detection performance with reduced computational complexity, it however suffers a significant deterioration in target detection performance in the presence of clutter. In this paper we provide evidence that the proposed mathematical model for SSC-GLRT detector outperforms the existing detectors in the presence of clutter. The performance analysis of the existing detectors and the proposed SSC-GLRT detector for MIMO radar in the presence of clutter are provided in this paper.

MIMO Radar Waveforms Using Orthogonal Complementary Codes with Doppler-Offset

2018 ◽  
Vol E101.B (6) ◽  
pp. 1503-1512
Author(s):  
Takaaki KISHIGAMI ◽  
Hidekuni YOMO ◽  
Naoya YOSOKU ◽  
Akihiko MATSUOKA ◽  
Junji SATO
Keyword(s):  
Mimo Radar ◽  
Radar Waveforms

Joint Angle, Velocity, and Range Estimation Using 2D MUSIC and Successive Interference Cancellation in FMCW MIMO Radar System

2020 ◽  
Vol E103.B (3) ◽  
pp. 283-290
Author(s):  
Jonghyeok LEE ◽  
Sunghyun HWANG ◽  
Sungjin YOU ◽  
Woo-Jin BYUN ◽  
Jaehyun PARK
Keyword(s):  
Interference Cancellation ◽  
Joint Angle ◽  
Mimo Radar ◽  
Radar System ◽  
Successive Interference Cancellation ◽  
Range Estimation

MIMO Radar Wide Band Array Range-Angle Imaging

PIERS Online ◽  
2009 ◽  
Vol 5 (1) ◽  
pp. 21-25 ◽  
Author(s):  
Changzheng Ma ◽  
Tat-Soon Yeo ◽  
Junjie Feng ◽  
Hwee Siang Tan
Keyword(s):  
Wide Band ◽  
Mimo Radar

Modeling and Analysis of the Clutter on Airborne MIMO Radar with Arbitrary Waveform Correlation

2011 ◽  
Vol 33 (3) ◽  
pp. 646-651 ◽  
Author(s):  
Xi-chuan Zhang ◽  
Wen-chong Xie ◽  
Yong-shun Zhang ◽  
Yong-liang Wang
Keyword(s):  
Mimo Radar ◽  
Modeling And Analysis ◽  
Arbitrary Waveform

Fast Transmit Beampattern Synthesis for MIMO Radar with Colocated Antennas

2010 ◽  
Vol 32 (2) ◽  
pp. 481-484 ◽  
Author(s):  
Liang-bing Hu ◽  
Hong-wei Liu ◽  
Xiao-chao Yang ◽  
Shun-jun Wu
Keyword(s):  
Mimo Radar ◽  
Beampattern Synthesis
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