Angle information assisted centralized multi-sensor multi-hypothesis tracking method

Abstract

The invention provides an angle information assisted centralized multi-sensor multi-hypothesis tracking (CMS-MHT) method, which is implemented through the following steps: (1) forecasting a flight path; (2) forming all possible flight path-measurement correlated hypothesises at the current moment, and calculating angle information assisted flight path scores; (3) pruning a flight path tree; and (4) carrying out multi-sensor filtering on the flight path. According to the invention, when measurement errors of the sensors are small, a flight path score which is in line with the actual situations is obtained by adopting an angle information assisted flight path score calculating method, so that the uncertainty of flight path-measurement correlated hypothesizes is reduced, and in comparison with a traditional CMS-MHT method, the method has the advantages that a better tracking effect is obtained, the track leakage rate is reduced, and the integrity of flight paths is enhanced.

Description

technical field [0001] The invention belongs to the field of target tracking and relates to a centralized multi-sensor multi-hypothesis tracking (CMS-MHT) method assisted by angle information. Background technique [0002] The data association methods currently used in centralized multi-sensor multi-target tracking are mainly extended from single-sensor multi-target tracking methods. For example, the centralized multi-sensor joint probabilistic data interconnection method (CMS-JPDA), the centralized multi-sensor multi-hypothesis tracking method (CMS-MHT), etc. The multi-hypothesis tracking (MHT) method can unify multiple links involved in multi-target tracking, such as track initiation, data association, track maintenance, and track termination, in one framework. When large and dense objects are involved, the MHT method is generally considered to be the best method for solving data association problems. Although the CMS-MHT algorithm has the same advantages, in a dense clu...

AI Technical Summary

Problems solved by technology

Although the CMS-MHT algorithm has the same advantages, in a dense clutter environment, due to the need to process measurements from multiple sensors at each moment, compared with the MHT method applied to a single sensor, the possible The number of track-measurement correlation assumptions is greatly increased, which increases the uncertainty of track-measurement correlation assumptions

However, the increase in the uncertainty of the track-measurement correlation assumptions is likely to cause false correlations, which ultimately leads to a decrease in the quality of the obtained track

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