Research On Joint TOA And DOA Estimation Algorithm In OFDM System

In recent years,orthogonal frequency division multiplexing(OFDM)technology has been widely used in positioning systems due to its characteristics of low complexity,high spectral efficiency,and resistance to multipath interference.In OFDM positioning system,time of arrival(TOA)and direction of arrival(DOA)joint estimation and positioning have the advantages of high estimation accuracy and small number of receiving nodes,and gradually become the main methods to complete accurate positioning.Therefore,the research on joint estimation algorithms for TOA and DOA in OFDM systems holds significant practical value.In this thesis,the joint estimation algorithm of TOA and DOA in OFDM system is mainly studied.The main contributions are as follows:1)When the OFDM system uses the MUSIC algorithm to perform joint estimation of TOA and DOA under the condition of low signal-noise ratio,the signal subspace and the noise subspace obtained by eigenvalue decomposition may not be completely orthogonal,which leads to errors in peak searching and degrades the performance of algorithm.In order to solve the problem,a joint TOA and DOA estimation algorithm based on the subspace weighting—WMUSIC algorithm is proposed.First,the algorithm uses the power series of noise eigenvalues to weight the noise subspace,and uses the reciprocal of signal eigenvalues to weight the signal subspace.Then,independent TOA and DOA estimates are obtained by spectral peak search.Finally,the joint TOA and DOA estimation is completed by constructing the cost function for parameter matching.The simulation results show that the proposed algorithm corrects the pseudo spectral function through weighting,effectively solving the problem of spectral peak aliasing caused by spectral peak search errors in the MUSIC algorithm.Compared with the MUSIC algorithm,the proposed algorithm has higher accuracy of TOA and DOA estimation.2)When using the root multiple signal classification(Root-MUSIC)algorithm for joint TOA and DOA estimation,a joint TOA and DOA estimation algorithm based on spectral decomposition—SF-Root-MUSIC algorithm is proposed due to the computational redundancy problem of the conjugate symmetric form of the roots obtained during the polynomial rooting process.Based on the structural characteristics of Laurent polynomials,the algorithm uses spectral decomposition to reduce the order of the root polynomial by half,reduces the computational complexity,completes independent TOA and DOA estimation,and completes joint estimation by constructing cost functions for parameter matching.The simulation results show that the proposed algorithm has similar estimation performance with Root-MUSIC algorithm,and can obtain higher TOA and DOA parameter estimation accuracy with lower complexity.3)When the number of array elements is maller than the number of multipath paths,a joint TOA and DOA estimation algorithm based on Nystr(?)m—Nystr(?)m-MUSIC algorithm is proposed.First,the algorithm extends the channel frequency response dimension.Then,Nystr(?)m algorithm is used to construct the approximate noise subspace,avoiding the construction of covariance matrix and eigenvalue decomposition process.Finally,the two-dimensional spectral function is constructed,the TOA and DOA joint estimation is completed through two-dimensional spectral peak searching.The simulation results demonstrate that compared to the existing algorithms,the proposed algorithm can effectively reduce the computational complexity on the basis of ensuring the estimation accuracy,and can complete the joint TOA and DOA estimation under the condition that the number of array elements is smaller than the number of multipath.