Research on Channel Optimization of Ads-B Aviation Target Surveillance Radar Based on Improved Filtering Algorithm

Xiaoxia Zheng, Bin Tang, Hongping Pu and Huihua Chen

Complexity, 2021, vol. 2021, 1-16

Abstract: In order to improve the surveillance effect of the aviation target surveillance radar, this paper improves the traditional filtering algorithm and builds the channel optimization system of the ADS-B aviation target surveillance radar based on the improved filtering algorithm. Moreover, this paper uses algorithm improvement to ensure the positive definite or semipositive definiteness of the state covariance and uses the root mean square volume Kalman filter to avoid the filter divergence or tracking interruption caused by the nonpositive definiteness of the matrix; the filtering principle of the interactive multimodel is to use multiple filters for parallel processing and achieve the adaptive adjustment algorithm residual error by adjusting the one-step prediction covariance in the adjustment algorithm. In addition, this paper combines the actual needs to construct a system functional structure to optimize the channel of the ADS-B aviation target surveillance radar and uses software engineering methods to model and analyze the requirements. Finally, this paper designs experiments to verify system performance. The research results show that the performance of the system constructed in this paper meets actual needs.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:9436589

DOI: 10.1155/2021/9436589

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