A new method of improving the weak target detection performance based on the MIMO radar

2006 ◽  
Author(s):  
Xi-Zeng Dai ◽  
Jia Xu ◽  
Ying-Ning Peng ◽  
Jia Xu ◽  
Xiang-Gen Xia
Keyword(s):  
Target Detection ◽  
Mimo Radar ◽  
Detection Performance ◽  
New Method ◽  
Weak Target

scholarly journals Target Detection Performance Analysis of FDA-MIMO Radar

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 164276-164285 ◽  
Author(s):  
Yu Zhu ◽  
Lei Liu ◽  
Zheng Lu ◽  
Shunsheng Zhang
Keyword(s):  
Performance Analysis ◽  
Target Detection ◽  
Mimo Radar ◽  
Detection Performance

A New Method for Radar High-Speed Maneuvering Weak Target Detection and Imaging

2014 ◽  
Vol 11 (7) ◽  
pp. 1175-1179 ◽  
Author(s):  
Shengqi Zhu ◽  
Guisheng Liao ◽  
Dong Yang ◽  
Haihong Tao
Keyword(s):  
Target Detection ◽  
High Speed ◽  
New Method ◽  
Weak Target

Target Detection Performance of Collocated MIMO Radar With One-Bit ADCs

2019 ◽  
Vol 26 (12) ◽  
pp. 1832-1836 ◽  
Author(s):  
Ziyang Cheng ◽  
Zishu He ◽  
Bin Liao
Keyword(s):  
Target Detection ◽  
Mimo Radar ◽  
Detection Performance

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.

Wideband Time-space Radon-Fourier Transform for High-speed and Weak Target Detection

2014 ◽  
Vol 35 (1) ◽  
pp. 15-23 ◽  
Author(s):  
Li-chang Qian ◽  
Jia Xu ◽  
Wen-feng Sun ◽  
Ying-ning Peng
Keyword(s):  
Fourier Transform ◽  
Target Detection ◽  
High Speed ◽  
Time Space ◽  
Weak Target

scholarly journals Implementation of a Modified Faster R-CNN for Target Detection Technology of Coastal Defense Radar

2021 ◽  
Vol 13 (9) ◽  
pp. 1703
Author(s):  
He Yan ◽  
Chao Chen ◽  
Guodong Jin ◽  
Jindong Zhang ◽  
Xudong Wang ◽  
...  
Keyword(s):  
False Alarm ◽  
False Alarm Rate ◽  
Target Detection ◽  
Real Data ◽  
Detection Performance ◽  
Detection Accuracy ◽  
Constant False Alarm Rate ◽  
Data Set ◽  
Detection Technology ◽  
Coastal Defense

The traditional method of constant false-alarm rate detection is based on the assumption of an echo statistical model. The target recognition accuracy rate and the high false-alarm rate under the background of sea clutter and other interferences are very low. Therefore, computer vision technology is widely discussed to improve the detection performance. However, the majority of studies have focused on the synthetic aperture radar because of its high resolution. For the defense radar, the detection performance is not satisfactory because of its low resolution. To this end, we herein propose a novel target detection method for the coastal defense radar based on faster region-based convolutional neural network (Faster R-CNN). The main processing steps are as follows: (1) the Faster R-CNN is selected as the sea-surface target detector because of its high target detection accuracy; (2) a modified Faster R-CNN based on the characteristics of sparsity and small target size in the data set is employed; and (3) soft non-maximum suppression is exploited to eliminate the possible overlapped detection boxes. Furthermore, detailed comparative experiments based on a real data set of coastal defense radar are performed. The mean average precision of the proposed method is improved by 10.86% compared with that of the original Faster R-CNN.

scholarly journals Clutter Cancellation and Long Time Integration for GNSS-Based Passive Bistatic Radar

2021 ◽  
Vol 13 (4) ◽  
pp. 701 ◽  
Author(s):  
Binbin Wang ◽  
Hao Cha ◽  
Zibo Zhou ◽  
Bin Tian
Keyword(s):  
Fourier Transform ◽  
Target Detection ◽  
Time Integration ◽  
Detection Performance ◽  
Bistatic Radar ◽  
Detection Range ◽  
Robust Detection ◽  
Coherent Integration ◽  
Long Time ◽  
Long Time Integration

Clutter cancellation and long time integration are two vital steps for global navigation satellite system (GNSS)-based bistatic radar target detection. The former eliminates the influence of direct and multipath signals on the target detection performance, and the latter improves the radar detection range. In this paper, the extensive cancellation algorithm (ECA), which projects the surveillance channel signal in the subspace orthogonal to the clutter subspace, is first applied in GNSS-based bistatic radar. As a result, the clutter has been removed from the surveillance channel effectively. For long time integration, a modified version of the Fourier transform (FT), called long-time integration Fourier transform (LIFT), is proposed to obtain a high coherent processing gain. Relative acceleration (RA) is defined to describe the Doppler variation results from the motion of the target and long integration time. With the estimated RA, the Doppler frequency shift compensation is carried out in the LIFT. This method achieves a better and robust detection performance when comparing with the traditional coherent integration method. The simulation results demonstrate the effectiveness and advantages of the proposed processing method.

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