A variational mode decomposition projectile signal processing algorithm of infrared sky screen velocity measurement system and detection mathematical model of detection screen

Li, Hanshan; Li, Ming; Ma, Yuju; Zheng, Yu; Li, S Z

doi:10.1016/j.ijleo.2023.171077

Cited by 3 publications

(1 citation statement)

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“…There are many existing studies on the recognition and processing of acoustic sensor signals, such as wavelet transform [15][16][17], support vector machine [18], and particle swarm optimization [19]. In [19], Jiang et al employed the wavelet transform filtering technique to process the output signal from acoustic sensors.…”

Section: Related Workmentioning

confidence: 99%

An Acoustic Array Sensor Signal Recognition Algorithm for Low-Altitude Targets Using Multiple Five-Element Acoustic Positioning Systems with VMD

Song,

2024

Applied Sciences

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To solve the problem in target acoustic signal processing and recognition when the target flies at a low altitude based on the acoustic positioning system, which is often affected by external interference and brings false information, this paper proposes a target signal processing and recognition algorithm for low-altitude target acoustic positioning based on variational modal decomposition and the test method of multiple five-element acoustic arrays. This algorithm uses VMD to decompose the target signal into modal components with different central frequencies and then performs wavelet threshold processing on the low-frequency part of the signal. After determining the remaining signal components and the low-frequency part’s threshold, the residual component is reconstructed. Based on the test principle and calculation model of the five-element acoustic positioning system, following processing of the low-altitude target acoustic positioning signal using variational modal decomposition, the cross-correlation function method is introduced to perform correlation operations on the basic array of five acoustic sensors and then obtain the time value and time difference of the target acoustic information in each acoustic sensor, ultimately determining the spatial position of the target. Finally, we used the data fusion processing method for target coordinates in multi-acoustic basic arrays to determine the actual target position. By comparing the results obtained using the high-speed camera method with those of the proposed approach, it was found that the average error in the test area of 100 × 100 m was less than 1 m.

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