基于Hough变换检测前跟踪的水下多目标被动检测方法

doi:10.12382/bgxb.2022.0290

摘要/Abstract

摘要：

无人潜航器集群的发展对水下目标探测产生了巨大挑战。针对水下多个低可探测目标检测问题和隐蔽性探测需求,提出一种基于Hough变换检测前跟踪的水下多目标被动检测方法。利用航空被动声纳浮标阵,构建水下无人潜航器被动检测模型;采用多枚被动声纳浮标自适应关联交叉定位技术,实现隐蔽检测前的数据预处理;采用双门限随机Hough变换检测前跟踪算法,实现水下高噪声密度条件下多目标的低可探测性的需求。仿真结果表明,该方法在低信噪比、多目标点迹交叉条件下具有较好的检测性能。

关键词: 水下多目标, 目标检测, 无人潜航器, 被动声纳, Hough变换, 检测前跟踪

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

王学敏, 于洪波, 张翔宇, 安舒, 李文海. 基于Hough变换检测前跟踪的水下多目标被动检测方法[J]. 兵工学报, 2023, 44(7): 2114-2121.

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.

图/表 11

图1 方法流程及核心内容

Fig.1 Method flow and core content

图2 浮标拦截阵探测水下目标示意图

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

图3 被动声纳浮标阵探测多目标示意图

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

图4 双门限随机HT-TBD多目标检测流程

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

表1 不同积累次数条件下的检测结果

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

图5 λ=100时检测示意图

Fig.5 Schematic diagram of detection when λ=100

图6 λ=200时检测示意图

Fig.6 Schematic diagram of detection when λ=200

表2 不同信噪比条件单/多目标检测概率

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

图7 目标点迹非交叉检测示意图

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

图8 目标点迹交叉检测示意图

Fig.8 Schematic diagram of crossing target point trace detection

表3 3种方法检测性能比较

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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