Research On Adaptive Time Delay Estimation Method For Pulsar Navigation

The pulsar is a special celestial body with extreme physical characteristics such as predictable rotation frequency and extremely stable cycle.It is called "Cosmic Lighthouse".Based on these characteristics,people have proposed an autonomous navigation technology based on X-ray pulsars,which can provide rich navigation information for spacecraft.In this navigation technology,the pulsar time delay is its core measurement.The accuracy of the PTDE(Pulsar Time Delay Estimation)and the real-time performance of the estimation directly affect the navigation performance of the navigation system.Therefore,it is the key to improve the performance of X-ray pulsar-based navigation technology by studying the fast and high precision PTDE algorithm.As a classic time delay estimation algorithm,the time delay estimation algorithm based on the adaptive filter can self-adaptively adjust its structure according to the external environment change,and exert the performance of the algorithm.Recursive Least Squares(RLS)is an adaptive algorithm with fast convergence rate and excellent robust performance.It is considered as the optimal solution to the least squares problem.However,its high performance is obtained at the cost of high computational complexity.Based on the deep research of RLS algorithm and the characteristics of pulse profiles,this paper proposes some improved algorithms based on RLS algorithm adaptive PTDE algorithm(RLSPTDE).Improved algorithms is as follows:(1)An adaptive PTDE algorithm based on fast RLS algorithm is proposed.In this paper,an adaptive PTDE model is established based on the Fast Transverse Filtering RLS(FTRLS)algorithm and the Stable Fast Transverse Filtering(SFTRLS)algorithm for PTDE.The fast RLS algorithm uses a fast transversal filter algorithm instead of the traditional RLS algorithm to calculate many matrix operations and Riccati equations,thereby reducing the complexity of the algorithm.The fast RLS algorithm consists of forward prediction,backward prediction,and joint estimation and the fast RLS algorithm is achieved by the parameter interchange of these three processes to maintaining a high PTDE accuracy.In addition,the SFTRLS algorithm makes the algorithm more stable by adding negative feedback redundancy,but the complexity of the algorithm is slightly higher than that of FTRLS.(2)An adaptive PTDE algorithm based on wavelet transform and RLS algorithmis proposed.The fast RLS algorithm reduces the PTDE performance of the RLS algorithm at low SNR.In order to make full use of the high performance of the RLS algorithm,this paper proposes to use the multi-level wavelet transform to preprocess the pulse profiles to obtain the low-frequency signal part of the pulse profiles,and then use the dynamic combination of two adaptive filters based on RLS algorithm to PTDE.The algorithm divides the PTDE process into wavelet transform preprocessing,global PTDE process and local PTDE process.Compared with RLSPTDE algorithm,the algorithm greatly reduces the complexity of the algorithm and further improves the PTDE accuracy.In the paper,the simulation data of the European Pulsar Network(EPN)and the actual data collected by the RXTE(Rossi X-ray Timing Explorer)satellite are used to simulate the above two methods,and compared with RLSPTDE.The experimental results show that the two algorithms proposed in this paper not only have high PTDE accuracy,but also greatly reduce the computational complexity.They have good performance in real-time and practicality.