组网雷达自适应模糊CFAR检测融合算法

doi:10.12305/j.issn.1001-506X.2022.01.14

Abstract

Abstract:

In order to improve the performance of constant false alarm rate (CFAR) detection of netted radar, based on fuzzy logic and maximum-censored mean level detector (MX-CMLD), an adaptive multi-sensor distributed fuzzy CFAR detection algorithm is proposed, which is a detection fusion algorithm based on no signal to noise ratio information. The CFAR detection is completed by transmitting the test statistics and detection reliability of the received signal of a single radar station. This method controls the amount of data transmitted to the fusion center through the voting module and feedback module, and adaptively selects the relevant radar data for fusion, which can achieve the management of radar resources to a certain extent. Simulation results show that the adaptive distributed fuzzy MX-CMLD has better detection performance in the background of uniform and multi-target interference.

Key words: target detection, netted radar, fuzzy logic, adaptive fusion

CLC Number:

TN957.51

Shufeng GONG, Weijun LONG, De BEN, Minghai PAN. Adaptive fuzzy CFAR detection fusion algorithm for netted radar[J]. Systems Engineering and Electronics, 2022, 44(1): 100-107.

Figures/Tables 16

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References 20

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项目	时刻1	时刻2	时刻3	时刻4	时刻5	时刻6	时刻7	时刻8
雷达1	1.000 0	1.400 0	1.960 0	2.646 1	3.434 7	3.510 3	3.510 3	3.601 5
雷达2	1.258 9	1.757 5	2.404 2	2.837 0	3.540 5	3.540 5	3.540 5	3.540 5
雷达3	7.943 3	3.610 6	3.610 6	3.521 8	3.521 8	3.550 0	3.550 0	3.516 3
雷达4	10.000 0	4.545 5	3.647 8	3.324 1	3.560 1	3.560 1	3.560 1	3.560 1
总能量	20.202 2	11.313 5	11.122 6	12.325 0	14.057 2	14.132 7	14.160 9	14.218 4
全局检测概率	1.000 0	0.995 0	0.987 0	0.996 0	1.000 0	1.000 0	1.000 0	1.000 0

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Adaptive fuzzy CFAR detection fusion algorithm for netted radar

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