TWS radar target spatial position grouping parallel tracking processing method

Abstract

The invention relates to a TWS radar target spatial position grouping parallel tracking processing method. The TWS radar target spatial position grouping parallel tracking processing method comprisesthe steps of: using a PowerPC (PPC for short) processing board as a hardware platform for method implementation; allocating a data preprocessing software unit and a target relevant filtering softwareunit in a target tracking main processing program into different CPU of the PPC board for parallel computing; grouping targets to be tracked by a TWS radar according to spatial positions, and evenly allocating the grouped targets into idle computing units on the PPC board for processing under the trigger of spatial detection azimuth data; and completing data exchange between the independent computing units on the PPC board by using a high-speed data transmission protocol RapidIO on the PPC board, and realizing parallel processing of TWS radar target tracking.

Description

technical field [0001] The invention relates to a TWS radar active data processing target tracking method. Background technique [0002] Active radar target tracking has experienced more than 50 years of development. Its basic idea was first proposed by Wax in 1955. In the early 1960s, Sittler deeply studied the multi-target tracking theory and data association and other issues, and achieved some important research results. In the early 1970s, Y.Bar-shalom and R.Singer pioneered the organic combination of data association technology and Kalman filter technology to conduct more in-depth research on target tracking, and made breakthrough progress. From the 1970s to the late 1980s, the multi-target tracking technology developed rapidly. Scholars represented by Y.Bar-Shalom, R.Singer, W.D.Blair, etc. made important breakthroughs in data association and maneuvering target tracking. Classical algorithms such as probabilistic data association filtering, multi-hypothesis tracking,...

AI Technical Summary

Problems solved by technology

[0004] With the increase of algorithm complexity and the diversity of input data, the combinatorial explosion of data has become the most difficult problem faced by active radar target tracking methods.

In the relevant treatises on radar active data processing, generally more complex correlation filtering algorithms, such as joint probability assignment algorithm, multi-hypothesis algorithm, etc., are described as time-consuming, computationally intensive, and difficult in engineering applications. It is difficult to put forward a series of application assumptions, reduce the integrity and complexity of the algorithm, and make the optimal algorithm drop to suboptimal or local optimum

But it is an undeniable fact that the performance of the algorithm has inevitably declined

Images