Fuzzy data association method in clutter environment and multi-target tracking method

Abstract

The invention provides a fuzzy data association method in a clutter environment. The fuzzy data association method comprises the following steps: step 1, establishing an interconnection matrix of candidate measurement and targets according to the distribution condition of measurement in a confirmation area; step 2, constructing a statistical distance through an interconnection rule; step 3, constraining the target function by utilizing KL divergence regular information; step 4, calculating the interconnection probability between each candidate measurement and different targets in the observation area through an iterative optimization algorithm; and step 5, updating the target state and the covariance by using probability weighting. The real-time performance of multi-target tracking is greatly improved, the multi-target tracking precision and the effective tracking rate of the method are similar to those of a classical joint probability data association algorithm, and the requirement for effective target tracking can be met. Correspondingly, the invention further provides a multi-target tracking method.

Description

technical field [0001] The invention relates to the technical field of target tracking, in particular to a fuzzy data association method and a multi-target tracking method in a clutter environment. Background technique [0002] The most important and difficult problem in multi-target tracking technology is how to carry out effective data association. Currently, the mainstream effective data association methods are: Joint Probabilistic Data Association (JPDA), Simple Joint Probabilistic Data Association (CJPDA), Multiple Hypothesis Tracking (MHT), Multiple Probability Hypothesis (MPH) and Particle Filtering. The above methods are all based on the idea of ​​probability and statistics, but in actual situations, there are false alarms and missed detections in the clutter environment, the actual sensor system always inevitably has measurement errors, and the prior knowledge of the tracking environment is difficult to count, etc. These uncertainties lead to ambiguity in the corre...

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Problems solved by technology

Another example is that the patent application number 201610942027.1 discloses a multi-target tracking method and tracking system suitable for clutter environments, which effectively solves the problem that the existing methods cannot provide new target states in the first few time steps after the new target appears. estimated problem

[0004] It can be seen that for the target tracking technology in the clutter environment, there are still many practical problems that need to be solved urgently in its practical application (such as improving target tracking performance, etc.) and there are still many specific solutions that have not been proposed.

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