Distributed multi-sensor fusion algorithm based on AMDs

Abstract

The invention discloses a distributed multi-sensor fusion algorithm based on AMDs. The algorithm comprises the following steps: S1, initializing system parameters; S2, using a constant false alarm detector to process radar echo information to obtain a measurement information set; S3, independently estimating a target state based on a kalman filter, S4, using high dimensional Gaussian distribution to represent the multi-objective joint posterior probability density; S5, carrying out the dimensionality reduction operation on the joint posterior probability density; S6, sending the AMD of each node to the adjacent nodes; S7, fusing the AMDs by using a generalized cross-covariance algorithm; S8, extracting the target state; S9, setting k = k + 1, if k>K, outputting the target state extracted in the S8 as a track; otherwise, returning to step S2. The distributed multi-sensor fusion algorithm realizes the joint fusion of a plurality of targets under the condition that the estimation errors of the different sensors are considered cross-correlated, has higher adaptability and better robustness, and effectively solves the problem of multi-target joint posteriori fusion in the traditional tracking system.

Description

technical field [0001] The invention belongs to the technical field of radar signal processing, in particular to an AMD-based distributed multi-sensor fusion algorithm. Background technique [0002] With the increasing complexity of the battlefield environment, the development of stealth technology and the continuous upgrading of electronic warfare, a single radar is far from meeting the requirements of the battlefield. Single-sensor detection and tracking face problems such as high false alarms, large missed detections, and discontinuous tracking, which lead to large-scale air defense loopholes in the national air defense network and threaten national security. The multi-radar cooperative detection system uses multi-radar sensors to observe targets from different dimensions such as azimuth, time, frequency, and polarization, and obtains more diverse and redundant target measurement information, and uses these complementary data to monitor moving targets. Tracking, so as to...

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Problems solved by technology

[0007] The purpose of the present invention is to overcome the deficiencies of the prior art, and provide a joint fusion of multiple targets under the condition of considering the estimation error cross-correlation of different sensors, which has higher adaptability and better robustness AMD-based distributed multi-sensor fusion algorithm that effectively solves the problem of multi-target joint posterior fusion in traditional tracking systems

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