Paper Info
Title
Fast Implementation Of Insect Multi-Target Detection Based On Multimodal Optimization
Abstract
Entomological radars are important for scientific research of insect migration and early warning of migratory pests. However, insects are hard to detect because of their tiny size and highly maneuvering trajectory. Generalized Radon-Fourier transform (GRFT) has been proposed for effective weak maneuvering target detection by long-time coherent detection via jointly motion parameter search, but the heavy computational burden makes it impractical in real signal processing. Particle swarm optimization (PSO) has been used to achieve GRFT detection by fast heuristic parameter search, but it suffers from obvious detection probability loss and is only suitable for single target detection. In this paper, we convert the realization of GRFT into a multimodal optimization problem for insect multi-target detection. A novel niching method without radius parameter is proposed to detect unevenly distributed insect targets. Species reset and boundary constraint strategy are used to improve the detection performance. Simulation analyses of detection performance and computational cost are given to prove the effectiveness of the proposed method. Furthermore, real observation data acquired from a Ku-band entomological radar is used to test this method. The results show that it has better performance on detected target amount and track continuity in insect multi-target detection.
Year
DOI
Venue
2021
10.3390/rs13040594
REMOTE SENSING
Keywords
DocType
Volume
generalized radon-fourier transform, particle swarm optimization, multimodal optimization
Journal
13
Issue
Citations 
PageRank 
4
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Rui Wang16720.39
Yiming Zhang200.34
Weiming Tian300.68
Jiong Cai421.75
Cheng Hu500.34
Tianran Zhang642.23