Non-myopic Scheduling Algorithm of Multi-platform Active/passive Sensors for Collaboration Tracking

doi:10.3969/j.issn.1000-1093.2019.01.014

Abstract

Abstract: A non-myopic scheduling algorithm of multi-platform active/passive sensors for collaboration tracking is proposed in order to track the maneuvering target in clutter and reduce the system emission risk. The non-myopic scheduling problem is formulated as a partially observable Markov decision process. The target belief state is updated by using the interactive multi-model and the probability data association algorithm, and the posterior Carmér-Rao lower bound is utilized to predict the non-myopic maneuvering target track accuracy. An improved Viterbi algorithm is proposed to search the optimal scheduling sequence. Simulated results show that the proposed search algorithm can be used to reduce the searching space and memory space, control the system emission cost and reduce the excessive sensor switching effectively.Key

Key words: non-myopicsensorscheduling, partiallyobservableMarkovdecisionprocess, interactivemulti-model, probabilitydataassociation, posteriorCarmér-Raolowerbound, Viterbialgorithm

CLC Number:

TN959.1⁺1

QIAO Chenglin， SHAN Ganlin， DUAN Xiusheng， GUO Feng. Non-myopic Scheduling Algorithm of Multi-platform Active/passive Sensors for Collaboration Tracking[J]. Acta Armamentarii, 2019, 40(1): 115-123.

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第40卷第1期
2019 年1月兵工学报ACTA
ARMAMENTARIIVol.40No.1Jan.2019

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