scholarly journals Compressive Sampling Method Using Resolution Limit on Direction Estimation for MIMO Radar

2012 ◽  
Vol 29 ◽  
pp. 3460-3465
Author(s):  
Peng Yuxing ◽  
Chen haowen ◽  
Xu Yi ◽  
Wang Hongqiang ◽  
Li Xiang
Keyword(s):  
Sampling Method ◽  
Mimo Radar ◽  
Compressive Sampling ◽  
Resolution Limit ◽  
Direction Estimation

Theoretical multidimensional resolution limit for MIMO Radar based on the Chernoff distance

2012 ◽  
Author(s):  
N. Duy Tran ◽  
Remy Boyer ◽  
Alexandre Renaux ◽  
Sylvie Marcos ◽  
Pascal Larzabal
Keyword(s):  
Mimo Radar ◽  
Resolution Limit ◽  
Chernoff Distance

scholarly journals On the Statistical Resolution Limit (SRL) for Time-Reversal based MIMO radar

2018 ◽  
Vol 144 ◽  
pp. 373-383 ◽  
Author(s):  
Messaoud Thameri ◽  
Karim Abed-Meraim ◽  
Foroohar Foroozan ◽  
Rémy Boyer ◽  
Amir Asif
Keyword(s):  
Time Reversal ◽  
Mimo Radar ◽  
Resolution Limit ◽  
Statistical Resolution

scholarly journals Statistical Angular Resolution Limit for Ultrawideband MIMO Noise Radar

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Xiaoli Zhou ◽  
Hongqiang Wang ◽  
Yongqiang Cheng ◽  
Yuliang Qin ◽  
Haowen Chen
Keyword(s):  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
Mimo Radar ◽  
Optimization Criterion ◽  
Ratio Test ◽  
Theoretic Approach ◽  
Resolution Limit ◽  
Factors Affecting ◽  
Noise Radar ◽  
The Relationship

The two-dimensional angular resolution limit (ARL) of elevation and azimuth for MIMO radar with ultrawideband (UWB) noise waveforms is investigated using statistical resolution theory. First, the signal model of monostatic UWB MIMO noise radar is established in a 3D reference frame. Then, the statistical angular resolution limits (SARLs) of two closely spaced targets are derived using the detection-theoretic and estimation-theoretic approaches, respectively. The detection-theoretic approach is based on the generalized likelihood ratio test (GLRT) with given probabilities of false alarm and detection, while the estimation-theoretic approach is based on Smith’s criterion which involves the Cramér-Rao lower bound (CRLB). Furthermore, the relationship between the two approaches is presented, and the factors affecting the SARL, that is, detection parameters, transmit waveforms, array geometry, signal-to-noise ratio (SNR), and parameters of target (i.e., radar cross section (RCS) and direction), are analyzed. Compared with the conventional radar resolution theory defined by the ambiguity function, the SARL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.

scholarly journals A Quadrilinear Decomposition Method for Direction Estimation in Bistatic MIMO Radar

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 13766-13772 ◽  
Author(s):  
Ziyi Wang ◽  
Changxin Cai ◽  
Fangqing Wen ◽  
Dongmei Huang
Keyword(s):  
Decomposition Method ◽  
Mimo Radar ◽  
Bistatic Mimo Radar ◽  
Direction Estimation

scholarly journals Three-Dimensional Extensions of Resolvability of Two Point Targets in MIMO Radar Using a Hypothesis Test Formulation

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ning Zhang ◽  
Jun Tang ◽  
Shuang Wan ◽  
Wei Zhu
Keyword(s):  
Hypothesis Test ◽  
Three Dimensional ◽  
Doppler Frequency ◽  
Mimo Radar ◽  
Broadband Noise ◽  
Closed Form Expression ◽  
Ratio Test ◽  
Three Dimension ◽  
Resolution Limit ◽  
Direction Of Departure

Multiple-input multiple-output (MIMO) radar has been extensively studied in recent years, due to its outstanding performance in various aspects. Resolution and estimation of the targets’ parameters are central capabilities of a MIMO radar system. In this paper, the resolution performance of MIMO radar in terms of the three-dimensional statistical resolution limit (3D SRL) is investigated, where three-dimension refers to direction of arrival (DOA), direction of departure (DOD), and Doppler frequency of a target. The scenario of two closely spaced targets corrupted by broadband noise with/without clutter sources is considered and the closed-form expression of the resolution threshold, which is the minimum signal-to-noise ratio (SNR) required for a given resolution performance, is derived using a generalized likelihood ratio test (GLRT) formulation. Finally, both theoretical and numerical analyses are provided for some insights regarding the resolution limit.

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