Abstract
Cross-spectrum signals can be calculated by the pressure signals. The sign distribution of cross-spectrum active component can be effectively used for target depth classification algorithm. The algorithm is applicable for depth classification of targets where frequencies can only excite the first two normal modes. The corresponding research results are mainly based on the theoretical study. There are few researches on the algorithm performance based on experiment results. To overcome this research lack, based on the effective depth model, the effects on various receiving depth, source frequency, and received signal-to-noise ratio on the algorithm performance have been studied in this paper. The influence of sound velocity profile parameters (negative gradient, thermocline intensity, thermocline thickness, and up-boundary depth) on the algorithm performance has also been researched. According to the simulation results, proper adjustment of the receiving depths can effectively improve the algorithm performance. The source frequency primarily affects the position of the ideal receiving depth which can be appropriately adjusted according to the depth classification requirements of the real sea environment. The algorithm performance improves gradually with the increase of signal-to-noise ratio. Moreover, the algorithm can also be applied under the conditions of negative gradient and thermocline. The comprehensive sound velocity profile parameters have a large impact on the depth classification performance of the algorithm. Even in the case of strong negative gradient or strong thermocline, the robustness of the algorithm is still high. The feasibility of our presented method has been verified by sea experiment. The practical application value of the ideal receiving depth has been researched and validated. The factors affecting the algorithm performance including line spectrum continuity and received signal-to-noise ratio have also been analyzed in our simulation and real sea experiments.
Highlights
The movement of underwater platforms in channel encounters the security threats caused by various targets
Sea depth is selected as H = 22 m; densities of seawater and sediment are ρ1 = 1:0g/cm3, ρ2 = 1:75g/cm3; sound velocity in the sediment is c2 = 1750m/s; source frequency is f = 120 Hz, and the range of source depth is 1~22 m
This paper analyzes the impact of receiving depth on the performance of the target depth classification algorithm through simulation and sea experiment
Summary
The movement of underwater platforms in channel encounters the security threats caused by various targets. The main research focus of this paper is to study a method for target depth classification, which is the method for target category classification. Source range and depth are obtained using a ray-based backpropagation algorithm by Felisberto et al [19] These depth classification algorithms have high accuracy, but most of these methods are not feasible to be applied in real application due to their high complexity and time consumption. Based on the sea experiment data processing results, this paper analyzes the influence of the ideal receiving depth concept on the performance of the algorithm while verifying the feasibility of the target depth classification algorithm. It shows the real application value of the ideal receiving depth concept. The paper makes an in-depth research about the affection of the sound velocity profile parameters (negative gradient, thermocline intensity, thermocline thickness, upboundary depth, etc.) on the algorithm performance
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