Dense multipath signal angle estimation method based on impulse response compression sensing

Abstract

The invention discloses a dense multipath signal angle estimation method based on impulse response compression sensing. A pseudo random sequence with the length of N as a baseband detection signal, aspatial channel impulse response model is determined, receiving array antennas that have the M same array elements and are arranged uniformly and linearly are generated, and a guide vector of the antenna array under a first path is determined; for receiving signals of from a first antenna element to an M antenna element, sliding correlation is carried out on the receiving signasl and a standard local pseudo-random sequence to obtain an observation impulse response, discretization processing is carried out to obtain an observation impulse response matrix, impulse response covariance matrixes ofeffective paths from the first one to the L one of the spatial channel are calculated respectively, a redundant dictionary for sparse reconstruction is constructed, and sparse vectors are calculatedto form an angular spatial spectrum, wherein the angle corresponding to the large value is the coherent path direct-of-arrival angle in the l-th path. Therefore, the direct-of-arrival angle estimationof lots of multi-path signals is realized; the estimation accuracy and the angular resolution are high; and the coherent paths are distinguished.

Description

technical field [0001] The invention belongs to the technical field of ranging and positioning in wireless communication systems, and in particular relates to a dense multipath signal angle estimation method based on impulse response compressed sensing. Background technique [0002] With the development of wireless communication technology, MIMO technology has become one of the main key technologies of current communication. As the communication medium and the basis of MIMO system optimization, the research and accurate description of the channel has become a current research hotspot. Accurate channel models are inseparable from effective spatial channel parameters, especially in complex scenarios such as dense multipath. At the same time, one of the preconditions for most of the existing high-precision angle-of-arrival estimation algorithms to achieve their super-resolution performance is that the number of multipaths is known. [0003] The existing angle of arrival estim...

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Problems solved by technology

[0003] The existing angle of arrival estimation algorithm has the following shortcomings: 1. The algorithm relies on the accurate information of the number of multipaths. If the number of multipaths is inaccurate, it will lead to false alarms or missing alarms during estimation, resulting in estimation errors ; 2. The algorithm has poor processing ability for the coherent path, because the coherent path causes a loss to the rank of the covariance matrix of the received signal, so the traditional estimation algorithm cannot correctly estimate the angle of arrival of the coherent path; 3. The receiving array Due to the limitation of the number of antenna apertures, the traditional algorithm requires that the number of multipaths is smaller than the number of oscillators in the antenna array, but the number of multipaths in the channel of the actual dense multipath scene is too large to meet the demand; 4. The angular resolution is insufficient, and the number of real channels The angle difference between the diameters is not large, requiring the algorithm to have a high angular resolution

[0004] Therefore, the traditional angle of arrival estimation algorithm is no longer suitable for dense multipath scenarios, and a new algorithm is needed to achieve correct multipath identification, multipath number estimation and multipath angle estimation

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