Long-Distance Aerial Target Detection Technology of Counter-UAV Image Seeker

doi:10.12382/bgxb.2021.0873

Abstract

Abstract:

Taking the low-cost counter-UAV guided munitions as the research object, this study focuses on long-distance UAV target detection, and the design of a local visual saliency-based clustering measurement algorithm. In this algorithm, the idea of local contrast measurement is introduced into the visible light image for the first time, and the detection of the target by measuring the spectral clustering of the local imaging domain is realized.More specifically, it measures the minimum distance between the average spectral value of the local image domain and the spectral values of adjacent pixels. In addition, to solve the multi-scale target problem, a corresponding multi-scale sliding window measurement method is designed.The brief flow of the whole algorithm is as follows: frequency-division median filtering was performed on the original RGB image frame; to better measure the spectral difference, the filtered RGB image was converted to the Lab color space; the sliding window model was used for UAV imaging domain search; the saliency detection method was adopted to measure the spectral difference to obtain a saliency measurement map; finally, a thresholding algorithm was used to obtain the pixel position of the potential UAV target. According to the UAV target imaging conditions, field shooting and artificial synthesis of long-distance UAV image datasets were carried out. The experimental results showed that the algorithm can successfully separate the UAV target from the background under various complex meteorological conditions.

Key words: counter-UAV technology, image seeker, saliency detection

ZHAO Fei, LOU Wenzhong, FENG Huanzhen, SU Zilong, WANG Jinkui, XUAN Weikun. Long-Distance Aerial Target Detection Technology of Counter-UAV Image Seeker[J]. Acta Armamentarii, 2023, 44(4): 1023-1033.

Figures/Tables 23

Fig.1 Schematic diagram of ballistic flight of counter-UAV guided munitions

Fig.2 Block diagram of UAV target detection algorithm

Fig.3 Typical median filter windows

Fig.4 Median filter processing effects

Fig.5 Sliding window model

Fig.6 Image patches vi and wi

Fig.7 Local visual saliency measurement algorithm

Fig.8 Multi-scale pixel domain measurement algorithm

Fig.9 RGB image to be detected

Fig.10 Multi-scale saliency measurement maps

Fig.11 Multi-scale measurement graph pooling results $\hat{S}$

Fig.12 Thresholding search algorithm

Fig.13 Dual-target image

Fig.14 Saliency measurement maps of two targets

Fig.15 Thresholding binary image

Fig.16 Guidance information diagram

Fig.17 Target imaging geometric model

Fig.18 Long-distance UAV imaging frame

Fig.19 Synthetic image

Fig.20 Test prototype

Table 1 Algorithm test results

测试图像	显著测量图	检测结果

Table 2 Algorithm test results

测试图像	显著测量图	检测结果

Table 3 Test data description

视频序号	帧数	单帧大小	目标大小	速度/ (帧·s^-1)	准确度/ %
1	50	640×512	<10×10	8	100
2	50	640×512	<10×10	8	100
3	50	640×512	<10×10	8	100
4	50	640×512	<10×10	8	100
5	50	640×512	<10×10	8	100

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