Batch Algorithm For Target Tracking On Passive Acoustic Detection Network

Passive acoustic detection network system locates and tracks targets using acoustic or infra-acoustic signal emitted by the emitter. Compared with active Radar system, it has the advantages of high security, all-weather and low cost. It is an important supplement for active radar. However, it has some problem in application, such as signal time delay, bearing only tracking and low detection, etc. In this paper, some batch type based algorithms and techniques are proposed for the above problem, especially for the passive acoustic detection target tracking in the condition of low detection probability. The main results and achievement in the paper are as follows:(1) The basic conception and principle of passive acoustic detection network are introduced briefly and some classical batch type tracking algorithms are given, such as pseudo-linear least squares,instrumental variables,maximum likelihood.(2) For the problem of low detection probability and serious information loss in passive acoustic detection system, we present a batch based acoustic network method to improve the detection ability. Due to the low detection probability, an acoustic sensor in the network maybe does not detect the target at some time; i. e. the measurement is not consecutive. We cumulate all measurement of the sensor network and process them by a sliding window batch technique. The fusion result can reach local optimization in the sense of least square.(3) For the problem of eliminating fake point when multiple cross flying targets are tracked in passive acoustic detection system, a joint maximum likelihood homology technique is proposed in this paper. Measurement data are cumulated spatially and divided homologous by a sliding window based on least squares batch algorithm.(4) The proposed batch algorithms are tested and verified on passive acoustic detection system simulation platform. Detailed performance analysis and comparison are given.