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Multi-target Positioning Method of Passive MIMO Radar based on DBSCAN

Published: 04 December 2020 Publication History

Abstract

In this paper, we propose a passive Multiple Input Multiple Output (MIMO) radar multi-target positioning method based on DBSCAN (Density-Based Spatial Clustering of Applications with Noise). MIMO radar has received extensive attention and researches since it has been introduced. Applying MIMO radar theory to passive radar technology can combine the advantages of the two technologies and get better detection performance. In this paper, the multi-target data association algorithm is mainly used, and the time delay information measured by multiple receiving stations is converted into distance information and associated with the cost matrix. First, data preprocessing is performed by eliminating data in the cost matrix which is greater than the threshold. Then DBSCAN clustering algorithm is used to divide the data into clusters. Finally, different clusters are weighted and fused to obtain multi-target position estimates. Simulation results prove that the algorithm performs well.

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    SPML '20: Proceedings of the 2020 3rd International Conference on Signal Processing and Machine Learning
    October 2020
    141 pages
    ISBN:9781450375733
    DOI:10.1145/3432291
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 04 December 2020

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    Author Tags

    1. DBSCAN
    2. MIMO radar
    3. data association
    4. multi-target positioning

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