Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration

被引:8
|
作者
Zhang, Xi [1 ]
Miao, Lingjuan [1 ]
Shao, Haijun [1 ]
机构
[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
基金
中国国家自然科学基金;
关键词
baseband signal preprocessing; dual-filter; state feedback; ultra-tight GPS/INS integration; navigation filter with expanded dimension;
D O I
10.3390/s16050627
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper.
引用
收藏
页数:22
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