Underwater Multi-Target Tracking Method

Abstract

Disclosed in the invention is an underwater multi-target tracking method. A wireless sensor network positioning system comprises a plurality of sensor nodes, a cluster head node and a control system. For the system positioning, an improved resampling non-augmented tasteless particle filtering algorithm is used to realize target positioning based on sensor network configuration. Because the algorithm fully utilizes information measured at current time at the current orientation to estimate a particle posterior probability density function, a defect that particle selection has blindness according to a PF algorithm is overcome, so that the approximate and better positioning precision can be realized under the circumstances that a few particles exist. Moreover, there is no need to expand the state dimension in a vector, so that the calculation complexity can be substantially reduced, the calculation time is improved, and the system can be realized in real time.

Description

technical field [0001] The invention relates to an underwater multi-target tracking method, in particular to an underwater multi-target tracking method based on an improved resampling non-dimensional expansion and tasteless particle filter algorithm, and belongs to the field of information technology. Background technique [0002] The positioning and tracking technology of underwater moving targets has a broad application background, involving military and civilian fields. In the traditional target passive positioning technology, the target passive positioning technology based on pure azimuth measurement is mostly used. The main problem to be solved is how to use the observed target azimuth information to estimate the target's motion parameters and then realize the target positioning and tracking. Most of the system configurations are airborne or shipborne single-station measurement systems. This system configuration is limited by the observability principle of moving target...

AI Technical Summary

Problems solved by technology

In recent years, international research in this direction has made remarkable achievements, among which particle filter (PF) has received more widespread attention, so in recent years, azimuth-only measurement and positioning technology based on particle filter method to achieve the goal has appeared , although this method has higher positioning accuracy than the method based on KF, but this method needs more particle numbers to realize the accurate estimation of the posterior probability, resulting in a large amount of calculation and long calculation time, which is not conducive to real-time application

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