Underwater Multi-target Detection Method Based on Hough Transform Track-before-detect Technique

doi:10.12382/bgxb.2022.0290

Abstract

Abstract:

The development of unmanned underwater vehicle cluster poses a great challenge to underwater target detection. Aiming at the detection problem of underwater multiple low detectable targets and the need for concealment detection, an underwater multi-target passive detection method based on Hough transform tracking before detection technique was proposed. Firstly, a passive detection model of unmanned underwater vehicle was constructed by using aviation passive sonar buoy array. Secondly, the adaptive correlation cross location technology of multiple passive sonar buoys was used to realize data preprocessing before concealment detection. Finally, the two-threshold randomized Hough transform track-before-detect algorithm was adopted to achieve effective detection of multi-targets with low detectability in high noise density conditions. Simulation results show that this method has good detection performance under the conditions of low signal-to-noise ratio with intersecting point traces of multiple targets.

Key words: underwater targets, target detection, unmanned underwater vehicle, passive sonar, Hough transform, track-before-detect

WANG Xuemin, YU Hongbo, ZHANG Xiangyu, AN Shu, LI Wenhai. Underwater Multi-target Detection Method Based on Hough Transform Track-before-detect Technique[J]. Acta Armamentarii, 2023, 44(7): 2114-2121.

Figures/Tables 11

Fig.1 Method flow and core content

Fig.2 Schematic diagram of buoy interception array for detecting underwater targets

Fig.3 Schematic diagram of passive sonar buoy array for detecting multiple targets

Fig.4 Multi-target detection flow of two-threshold randomized HT-TBD

Table 1 Results obtained after different times of accumulation

检测概率和运算时间	N_a
检测概率和运算时间	3	4	5	6	7	8
检测概率/%	58.3	67.2	78.3	82.1	83.5	83.1
运算时间/s	1.11	1.14	1.21	1.35	1.57	1.71

Fig.5 Schematic diagram of detection when λ=100

Fig.6 Schematic diagram of detection when λ=200

Table 2 Statistics of single/multi-target detection probability under different SNR conditions

目标	信噪比/dB
目标	1	2	3	4	5	6	7	8	9	10
单目标	10	40	72	73	75	79	81	83	85	86
多目标	0	18	61	62	66	67	69	71	73	74

Fig.7 Schematic diagram of non-crossing target point trace detection

Fig.8 Schematic diagram of crossing target point trace detection

Table 3 Performance comparison of three detection methods

信噪比/ dB	检测概率/%			平均运行时间/s
信噪比/ dB	DP- TBD	HT- TBD	本文方法	DP- TBD	HT- TBD	本文方法
3	49.2	47.3	60.1	2.51	3.12	1.71
5	52.7	53.4	63.6	2.38	2.65	1.42
10	68.3	66.6	71.5	2.33	2.32	1.34

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