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- Publisher
- Cambridge University Press
- Copyright
- Copyright © The Author(s), 2025. Published by Cambridge University Press on behalf of The Royal Institute of Navigation
- ISSN
- 1469-7785
- eISSN
- 0373-4633
- DOI
- 10.1017/S0373463324000341
- Publisher site
- See Article on Publisher Site
Abstract
Abstract Aiming at the error estimation problem of a radar detection system when the variation law of system error is unknown, an improved Gaussian mean-shift radar dynamic error registration algorithm (IGMSR) is proposed. The algorithm can effectively adapt to the variation of system error when the variation law of system error is unknown. The IGMSR algorithm uses the mean-shift method to contribute different characteristics to the estimation results of different sample points, and constructs weight coefficients according to the deviation of sample points from the mean and sampling time. The simulation results show that more than 90% of the constant system errors can be eliminated; for the systematic error with slow change, more than 80% of the bias can be eliminated in real time, while a previous method of Zhu and Wang (2018) can only eliminate 60% of the systematic error and require the change law to be known. This method overcomes the influence of random error and abnormal point, and the estimation results are more robust.
Journal
Journal of Navigation – Cambridge University Press
Published: Jul 1, 2024
Keywords: radar registration; dynamic bias; bias estimate; mean shift