High Resolution Multipath Time Delay Estimation Based on FLOCCS-ESPRIT

The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.

Multipath Time Delay Estimation Based on MUSIC Algorithm Under Small Sample Conditions

On account of the traditional multiple signal classification(MUSIC)algorithm has poor performance in time delay estimation under the condition of small sampling data and low SNR.In this paper,the traditional MUSIC algorithm is improved.The algorithm combines the idea of spatial smoothing,constructs a new covariance matrix using the covariance information of the measurement data,and constructs a weighted value using the modified noise eigenvalues to weight the traditional estimation spectrum.Simulation results show that the improved algorithm has steeper spectral peaks and better time delay resolution under the condition of inaccurate path number estimation.The time delay estimation accuracy of this algorithm is higher than that of the traditional MUSIC algorithm and the improved SSMUSIC algorithm under the conditions of small sampling data and low SNR.

Multipath tracking with LTE signals for accurate TOA estimation in the application of indoor positioning

Indoor positioning with high accuracy plays an important role in different application scenar-ios.As a widely used mobile communication signal,the Long-Term Evolution(LTE)network can be well received in indoor and outdoor environments.This article studies a method of using different reference signals in the LTE downlink for carrier phase time of arrival(TOA)estimation.Specifically,a solution is proposed and a multipath tracking Software Defined Receiver(SDR)is developed for indoor positioning.With our SDR indoor positioning system,the pilot signals of the LTE signals are firstly obtained by the coarse synchronization and demodulation.Then,with the assistance of the pilot signals,the time delay acquisition,the multipath estimating delay lock loop(MEDLL)algorithm,and the multipath anomaly detection are sequentially carried out to obtain navigation observations of received signals.Furthermore,to compare the perfor-mance of different pilot signals,the Secondary Synchronous Signals(SSS)and Cell Reference Signals(CRS)are used as pilot signals for carrier phase-based TOA estimation,respectively.Finally,to quantify the accuracy of our multipath tracking SDR,indoor field tests are carried out in a conference environment,where an LTE base station is installed for commercial use.Our test results based on CRS show that,in the static test scenarios,the TOA accuracy measured by the 1-σerror interval is about 0.5 m,while in the mobile environment,the probability of range accuracy within 1.0 m is 95%.