Automatic Planning Method for Underwater Vehicles Considering the Influence of Multiple Environmental Factors

doi:10.12382/bgxb.2024.1129

Abstract

Abstract:

The proposed method addresses the issue of insufficient conceal and poor robustness in path planning for underwater vehicles in complex marine environments,where current methods only consider hydrological conditions for stealth planning.This method first calculates the instantaneous detection probability of the underwater vehicle influenced by the hydrological environment by integrating the sonar equation with the Bellhop model and using temperature and salinity data.It then incorporates the models of target lateral distance and patrol width,combined with terrain data,to obtain the probability of detection platforms constrained by geographical factors and the sonar contact time.Finally,it integrates these two aspects to construct a concealment effectiveness model that takes into account the influence of multiple environmental factors.Finally,an A^* algorithm that considers concealment is used to automatically calculate the concealed route.Experimental results show that,compared to traditional concealment planning methods,the proposed method integrates hydrological and geographical factors into a normalized stealth effectiveness value and applies it to the stealth planning algorithm,which significantly reduces the average cumulative detection probability of the vehicle when navigating complex straits,enhancing the concealment of the planned route; results in a more robust concealment route that better meets practical application requirements.

Key words: underwater vehicles, concealed route, sonar detection, automatic planning, cumulative detection probability

ZHANG Gengming, ZHANG Lihua, WANG Yitao, ZHOU Yinfei, DAI Zeyuan. Automatic Planning Method for Underwater Vehicles Considering the Influence of Multiple Environmental Factors[J]. Acta Armamentarii, 2025, 46(11): 241129-.

Figures/Tables 13

Fig.1 Schematic diagram of model construction process

Fig.2 Schematic diagram of the target lateral range model

Fig.3 Schematic diagram for selecting the first and second shortest distances

Fig.4 Distribution map of patrol width in the ocean area

Fig.5 The detection probability of fixed sonar for targets at a depth of 30m in October

Fig.6 Overall three-dimensional concealment effectiveness of CMF in October

Fig.7 Schematic diagram of path planning algorithm

Fig.8 The CHF concealment effectiveness of the 30-meter layer during four seasons.

Fig.9 The CMF concealment effectiveness of the 30-meter layer during four seasons.

Fig.10 Experiment path planning results and detection force diagram

Fig.11 Histogram of path lengths covered by the detection range of the mobile platform for each path in Experiment during four seasons.

Table 1 The average cumulative detection probability corresponding to each path in the experiment

方法	春季	夏季	秋季	冬季	均值	标准差
CHF	0.2815	0.1585	0.1528	0.8124	0.3513	0.3131
CMF	0.0663	0.0976	0.1523	0.1060	0.1056	0.0355

Table 2 Length of each path in the experiment km

方法	春季	夏季	秋季	冬季	均值
CHF	894.7	918.2	998.8	866.1	919.45
CMF	602.1	594.4	719.6	717.4	658.4

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