Hybrid particle filtering algorithm for GPS multipath mitigation

An altemative algorithm for mitigating GPS multipath was presented by integrating unscented Kalman filter （UKF） and wavelet transform with particle filter. Within consideration of particle degeneracy, UKF was taken for drawing particle. To remove the noise from raw data and data processing error, adaptive wavelet filtering with threshold was adopted while data preprocessing and drawing particle. Three algorithms, named EKF-PF, UKF-PF and WM-UKF-PF, were performed for comparison. The proposed WM-UKF-PF algorithm gives better error minimization, and significantly improves performance of multipath mitigation in terms of SNR and coefficient even though it has computation complexity. It is of significance for high-accuracy positioning and non-stationary deformation analysis.

Receiver-channel based adaptive blind equalization approach for GPS dynamic multipath mitigation

Aiming at mitigating multipath effect in dynamic global positioning system （GPS） satellite navigation applications, an approach based on channel blind equalization and real-time recursive least square （RLS） algorithm is proposed, which is an application of the wireless communication channel equalization theory to GPS receiver tracking loops. The blind equalization mechanism builds upon the detection of the correlation distortion due to multipath channels; therefore an increase in the number of correlator channels is required compared with conventional GPS receivers. An adaptive estimator based on the real-time RLS algorithm is designed for dynamic estimation of multipath channel response. Then, the code and carrier phase receiver tracking errors are compensated by removing the estimated multipath components from the correlators＇ outputs. To demonstrate the capabilities of the proposed approach, this technique is integrated into a GPS software receiver connected to a navigation satellite signal simulator, thus simulations under controlled dynamic multipath scenarios can be carried out. Simulation results show that in a dynamic and fairly severe multipath environment, the proposed approach achieves simultaneously instantaneous accurate multipath channel estimation and significant multipath tracking errors reduction in both code delay and carrier phase.

GPS short-delay multipath estimation and mitigation based on least square method

The GPS multipath signal model is presented, which indicates that the coherent DLL outputs in multipath environment are the convolution between the ideal DLL outputs and the channel responses. So the channel responses can be estimated by a least square method using the observed curve of the DLL discriminator. In terms of the estimated multipath channels, two multipath mitigation methods are discussed, which are equalization filtering and multipath subtracting, respectively. It is shown, by computer simulation, that the least square method has a good performance in channels estimation and the multipath errors can be mitigated almost completely by either of the methods. However, the multipath subtracting method has relative small remnant errors than equalization filtering.

Multipath mitigation method based on Gaussian mixture model in RF relative measurement

Radio Frequency(RF) technology represents a high-precision relative navigation solution that has significant potential for application to earth-orbiting satellites. In precision applications, multipath errors dominate the total error because observables, which are used to estimate carrier-phase integer ambiguity, are not always subject to a Gaussian distribution when dualfrequency ambiguity estimation methods are used in the presence of multipath. As it has been shown that ranging observables obey a Gaussian mixture distribution, this study proposes improvements to the accuracy of estimation based on multipath mitigation founded on the Gaussian mixture model. To this end, such a model is created for integer ambiguity resolution in the presence of multipath, using which the theoretical error in dual-frequency ambiguity estimation is derived.Expectation Maximization(EM), which aids dual-frequency ambiguity estimation, is subsequently proposed to reduce the effect of multipath errors. Finally, two experimental scenarios are implemented to test the performance of the proposed method. The results show that EM-aided dualfrequency ambiguity estimation reduces the range error to approximately 20% in comparison with simple dual-frequency ambiguity estimation. Therefore the proposed technique is effective for multipath mitigation in RF relative measurement.

A multipath mitigation algorithm for GNSS signals based on the steepest descent approach

Multipath interference seriously degrades the performance of Global Navigation Satellite System(GNSS)positioning in an urban canyon.Most current multipath mitigation algorithms suffer from heavy computational load or need external assistance.We propose a multipath mitigation algorithm based on the steepest descent approach,which has the merits of less computational load and no need for external aid.A new ranging code tracking loop is designed based on the steepest descent method,which can save an early branch or a late branch compared with the narrow-spacing correlation method.The power of the Non-Line-of-Sight(NLOS)signal is weaker than that of the Line-of-Sight(LOS)signal when the LOS signal is not obstructed and with a relatively high Carrier Noise Ratio(CNR).The peak position in the X-axis of the ranging code autocorrelation function does not move with the NLOS interference.Meanwhile,the cost function is designed according to this phenomenon.The results demonstrate that the proposed algorithm outperforms the narrow-spacing correlation and the Multipath Estimated Delay Locked Loop(MEDLL)in terms of the code multipath mitigation and computation time.The Standard Deviation(STD)of the tracking error with the proposed algorithm is less than 0.016 chips.Moreover,the computation time of the proposed algorithm in a software defined receiver is shortened by 24.21%compared with the narrow-spacing correlation.

Review for Multipath Facts in the Realm of Weak GNSS Signal

One of the most significant problem pending to be mitigated for satellite navigation at indoor environments is the multipath errors. At indoor environments, weak GNSS signals should be acquired and tracked by the GPS receivers, this paper will give a review of the facts in multipath and its main influence in the GNSS navigation systems. Investigation in this field are not new, understanding and mitigating multipath effects on GPS receivers will lead to an important level where the system can be used within a desired tolerance reducing its errors due to more accurate positioning solution.

Multi-antenna synchronized global navigation satellite system receiver and its advantages in high-precision positioning applications

The multi-antenna synchronized global navi- gation satellite system receiver is a high precision, low cost, and widely used emerging receiver. Using this type of receiver, the satellite and receiver clock errors can be eliminated simultaneously by forming between antenna single-differences, which is equivalent to the conventional double-difference model. However, current multi-antenna synchronized global navigation satellite system receiver products have not fully realized their potential to achieve better accuracy, efficiency, and broader applications. This paper introduces the conceptual design and derivable products of multi-antenna synchronized global navigation satellite system receivers involving the aspects of attitude determination, multipath effect mitigation, phase center variation correction, and ground-based carrier phase wind- up calibration. Through case studies, the advantages of multi-antenna synchronized global navigation satellite system receivers in high-precision positioning applications are demonstrated.