Optimization method of adaptive differential evolution algorithm for passive radar station distribution

The invention discloses an optimization method of an adaptive differential evolution algorithm for passive radar station arrangement. Establishing a passive time difference station distribution simulation scene; 2, initializing a population; 3, calculating a fitness value; step 4, genetic manipulati...

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Hauptverfasser:	WANG ZHAO, RONG YAN, LI PENG, LIU GAOGAO
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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creator	WANG ZHAO RONG YAN LI PENG LIU GAOGAO
description	The invention discloses an optimization method of an adaptive differential evolution algorithm for passive radar station arrangement. Establishing a passive time difference station distribution simulation scene; 2, initializing a population; 3, calculating a fitness value; step 4, genetic manipulation; according to the method, on one hand, the differential evolution algorithm can solve the problems of many variable parameters and complex parameter setting of the particle swarm algorithm, and the iteration times, the fitness value and the weight factors are fused in the aspect of parameter generation, so that the search and convergence of the algorithm are more reasonable; the influence of the communication distance between the station address error, the time difference error and the observation stations on the station distribution result is considered, so that the modeling process is more realistic. 本发明公开了一种自适应差分进化算法用于无源雷达布站的优化方法，包括以下步骤；建立无源时差布站仿真场景；步骤2：种群的初始化；步骤3：适应度值计算；步骤4：遗传操作；本发明一方面是差分进化算法可以解决粒子群算法可变参数多，参
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Establishing a passive time difference station distribution simulation scene; 2, initializing a population; 3, calculating a fitness value; step 4, genetic manipulation; according to the method, on one hand, the differential evolution algorithm can solve the problems of many variable parameters and complex parameter setting of the particle swarm algorithm, and the iteration times, the fitness value and the weight factors are fused in the aspect of parameter generation, so that the search and convergence of the algorithm are more reasonable; the influence of the communication distance between the station address error, the time difference error and the observation stations on the station distribution result is considered, so that the modeling process is more realistic. 本发明公开了一种自适应差分进化算法用于无源雷达布站的优化方法，包括以下步骤；建立无源时差布站仿真场景；步骤2：种群的初始化；步骤3：适应度值计算；步骤4：遗传操作；本发明一方面是差分进化算法可以解决粒子群算法可变参数多，参</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230407&DB=EPODOC&CC=CN&NR=115935709A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230407&DB=EPODOC&CC=CN&NR=115935709A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG ZHAO</creatorcontrib><creatorcontrib>RONG YAN</creatorcontrib><creatorcontrib>LI PENG</creatorcontrib><creatorcontrib>LIU GAOGAO</creatorcontrib><title>Optimization method of adaptive differential evolution algorithm for passive radar station distribution</title><description>The invention discloses an optimization method of an adaptive differential evolution algorithm for passive radar station arrangement. 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subjects	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
title	Optimization method of adaptive differential evolution algorithm for passive radar station distribution
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