A Novel Adaptive Recursive Least Squares Filter Algorithm of SINS/SAR Integrated Navigation Systems

Lu Zhang, Yunjie Qu, Wenhui Wang, Bangqing Li, Kai Yu

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

1 Citation (Scopus)

Abstract

In strapdown inertial navigation system (SINS) synthetic aperture radar (SAR) integrated navigation systems, the time-varying parameter estimation is a challenging problem because SAR measurements are fairly few and have unequal interval. In such case, the common Kalman filter algorithm can't be convergent. Furthermore, the traditional recursive least squares (RLS) algorithm is difficult to estimate the time-varying parameter. This paper proposed a novel adaptive square root recursive least squares (ASRRLS) filter algorithm of SINS/SAR integrated navigation systems. The first characteristic of ASRRLS is introducing adaptive fading factors based on the orthogonality principle, which can effectively track the parameters' varying. The second characteristic of ASRRLS is taking covariance square root matrix instead of covariance one in the filter algorithm, which can avoid filtering divergence and improve the filter convergence speed. The ASRRLS filter algorithm is deduced and the performance is rigorously analyzed. Simulation results demonstrate the feasibility and effectiveness of the proposed approach.
Original languageEnglish
Title of host publication2010 3rd International Symposium on Systems and Control in Aeronautics and Astronautics
PublisherIEEE Explore
Pages1142-1145
Number of pages4
ISBN (Electronic)978-1-4244-6045-8, 978-1-4244-7505-6
ISBN (Print)978-1-4244-6043-4
DOIs
Publication statusPublished - 2010
Event3rd International Symposium on Systems and Control in Aeronautics and Astronautics - Harbin, China
Duration: 8 Jun 201010 Jun 2010

Conference

Conference3rd International Symposium on Systems and Control in Aeronautics and Astronautics
Abbreviated titleISSCAA 2010
Country/TerritoryChina
CityHarbin
Period8/06/1010/06/10

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