The antenna array technology, especially the spaced-time array processing (STAP), is one of the effective methods used in Global Navigation Satellite System (GNSS) receivers to refrain the power of jamming and enhance the performance of receivers in the circumstance of interference. However, biases induced to the receiver because of many reasons, including characteristic of antennas, front-end channel electronics, and space-time filtering, are extremely harmful to the high precise positioning of receivers. Although plenty of works have been done to calibrate the antenna and to mitigate these biases, achieving a good performance of antijamming, high accuracy, and low complexity at the same time still remains challenging. Different from existing works, this paper leverages the characteristic of GNSS signal’s Doppler frequency in STAP, which is proven to remain unbiased to solve the problem, even when the nonideal antennas are used and the interference circumstance changes. Since the integration of frequency is carrier phase, the unbiased Doppler frequency leads to an accurate estimation of carrier phase which can be used to calibrate the antenna array without extra apparatus or complicating algorithms. Therefore, a simple Doppler-aid strategy may be developed in the future to solve the difficulty of STAP bias mitigation.
Radio frequency interference has become a rising problem to the signal of the Global Navigation Satellite System (GNSS). An effective way to achieve anti-jamming is by using an antenna array in GNSS signal processing. However, antenna array processing will cause a decline in the accuracy of pseudo-range measurements because of the channel mismatch and some other non-ideal factors. To solve this problem, space–time or space–frequency adaptive array processing is widely used for interference cancellation while constraining the delay of each antenna at the same time. In this paper, an anti-jamming algorithm with a time-delay constraint is proposed, where one antenna is chosen as the reference and data from other antennas is corrected based on the signal received from it. The deduction and simulation results show that the proposed algorithm can effectively improve the accuracy of pseudo-range measurements without degradation of anti-jamming performance.
In radar signal processing, radar target parameter estimation is one of the important tasks of radar target detection. Multipath effect is one of the main error sources of satellite navigation system. In the existing research, the method based on maximum likelihood estimation criterion is considered as the best multipath suppression technology, but its calculation is particularly complicated when there are multiple signals and the number of paths is unknown. This paper mainly studies the application of sparse representation theory in radar target parameter estimation, taking Doppler frequency estimation as an example. The sparse model of Doppler frequency estimation is established, and the frequency estimation is carried out by the classical greedy iterative reconstruction algorithm, and high resolution is obtained. In this paper, a variable step-size fitting algorithm is adopted, which is simple and practical, has little computation, is independent of multipath number, is easy to realize and is easy for real-time signal processing.
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