Passive multi-station multi-target direction-finding cross location method based on angle information

Abstract

The invention belongs to the technical field of electronic countermeasures, and specifically relates to a passive multi-station multi-target direction-finding cross location method based on angle information. The passive multi-station multi-target direction-finding cross location method based on angle information includes the steps: by means of a multi-radiation-source data association algorithm,associating the observation data of multiple observation stations to obtain a cost matrix C(p,q), and then according to the obtained cost matrix C(p,q), estimating the target coordinates by means of ak-mean value++clustering algorithm. The passive multi-station multi-target direction-finding cross location method based on angle information has the advantages of being able to accurately associating the data of multiple stations and finally accurately estimate the position of the target, being simple, and having preferable effect.

Description

technical field [0001] The invention belongs to the technical field of electronic countermeasures, and in particular relates to a passive multi-station multi-target direction-finding cross-location method based on angle information. Background technique [0002] In the process of electronic reconnaissance, accurately estimating the position of the target radiation source is helpful to obtain the information of the radiation source. It is the key and main basis for high-level situation estimation and threat estimation, and it is also an important guarantee for achieving precise strikes on the target. With the increasing complexity of the electromagnetic environment, the positioning requirements are also increasing, and domestic and foreign scholars are also deepening the research on direction finding cross positioning. In the passive positioning system, direction finding cross-location is produced along with electronic countermeasures, and it is the most widely used and the l...

AI Technical Summary

Problems solved by technology

At present, multi-station and multi-target direction-finding cross positioning is faced with the following problems: 1) When using multi-station coordinated positioning, how to distinguish which of the measurement data of each passive station comes from the same target, and combine the measurement data belonging to the same target (that is, to complete the measurement data association), and then target positioning can be performed; if the association is incorrect, false targets will appear; 2) With the increase in the number of targets, multiple passive observation stations will produce a large number of false intersections, how to quickly and efficiently Removing spurious intersections of

Since data clustering using the k-means algorithm needs to know the number of clusters and the initial cluster center point, but in actual situations, the number of clusters and the initial cluster center point are often not known in advance, so the proposed k -Means++ algorithm to solve the problem about the initial center has become a standard of hard clustering algorithm, but the research of clustering algorithm represented by k-means++ clustering method in passive positioning is currently It is still very little, and it is a direction worthy of research

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