Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration  
[PERSON]  
1 School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China;  
[EMAIL_ADDRESS] (L.M. ); [EMAIL_ADDRESS] (H.S.) 1  
[PERSON]  
1 School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China;  
[EMAIL_ADDRESS] (L.M. ); [EMAIL_ADDRESS] (H.S.) 1  
[PERSON]  
1 School of Automation, Beijing Institute of Technology (BIT), Beijing 100081, China;  
[EMAIL_ADDRESS] (L.M. ); [EMAIL_ADDRESS] (H.S.) 1  
Footnote 1: email: 1  
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channel and navigation parameters together [4; 5], and in the other case, each channel has a baseband signal pre-filter which estimates the tracking parameters for itself, and the integrated navigation filter just needs to estimate the navigation parameters. The second category is actually a form of federated filtering, and usually has higher computational efficiency [6; 7; 8]. The baseband signal preprocessing realizes optimal estimation of signal characteristic quantities by KF. Thus, under the application background of the ultra-tight GPS/INS integration, it can restrain phase noise more effectively than the loop filter of the classical GPS tracking channel [9; 10]. For each channel, the baseband signal preprocessing is generally completed by a single pre-filter [11]. Both carrier tracking errors and code tracking errors are included in the state vector, namely, these two kinds of tracking errors are tightly coupled through the state and observation equations. However, the precision of carrier and code loops do not have the same order of magnitude. The code loop has great tolerance for tracking errors due to the long wavelength of CA code, while the carrier loop is much more sensitive [12; 13]. As preprocessing continues, the code tracking errors would be delivered to the carrier loop and cause the degradation of carrier tracking precision or even loss of lock. In addition, even if the baseband signal preprocessing is applied in a GPS receiver, the Doppler shifts estimated under highly dynamic conditions may still contain significant errors. In the ultra-tight GPS/INS integration, these incorrect GPS outputs eventually lead the estimation of INS errors to be contaminated [14]. That generally means the whole system suffers performance degradation, or even completely crashes. To solve these problems, this paper makes creative contributions in both the tracking and navigation domain. Two independent pre-filters with state feedback are constructed to replace the classical loop filters. The advantages of decoupling between carrier tracking and code tracking are analyzed in detail. Since the single-filter and dual-filter preprocessing models are constructed based on the same principle, their comparison can be free from the influence of other factors. In fact, compared with a popular error-state pre-filter, even the single-filter model has better tracking performance due to the benefits of state feedback. In the ultra-tight GPS/INS integration, local carrier generation is still controlled by state feedback, and the carrier frequency derived from the external navigation information is just used to correct the state feedback value. Meanwhile, a specific integrated navigation filter is presented by taking the pseudorange rate estimation error in each channel as the additional state variable. This scheme ensures the estimation of original state variables, especially the INS errors, is immune to these GPS tracking errors, and hence enables the integrated system to maintain high accuracy even when GPS receiver operates under harsh conditions. The rest of this paper is organized as follows: first, a baseband signal preprocessing model is designed based on a dual-filter structure, while the state feedback control values of carrier and code loops are derived in detail.