Research On Joint Doa-delay Estimation Methods For Space-time Distributed Siganls

In complicated wireless communication environment, the user signals cause multipath propagation phenomenon through refraction, diffraction and scatting, which leads to the inter-symbol interference and co-channel interference of space angular spread and the time-delay spread, respectively, these interferences are important reasons affecting the quality of modern wireless mobile communication. In wireless mobile communication system, space-time joint processing technology can be used effectively to inhibit signal multipath transmission, enlarge the system capacity and improve the quality of communication, which is both theoretical and applicable.In this thesis, with the wireless communication environment multipath transmission as the main research object, we will deeply analyze the existing channel model, the joint space-time distributed multipath cluster signal parameter estimation algorithm is improved and a new estimation method is proposed. The main content of the thesis are as follows:The thesis deduces the space-time distributed multipath signal channel model of a known distributed function, and analyses the coherent relationship between the space-time channel noise along with the noise variance form after discrete fourier transform and deconvolution, and it turns out that after deconvolution calculation of traditional joint space-time parameters estimation can make a large the channel noise variance, affecting the signal subspace and makes the estimation inaccurate.An improved method is proposed for the problem. Constructed the space propagator and time-delay propagator by calculating the spatial covariance matrix and time-delay covariance matrix, respectively, and search out the space-time parameters joint estimation using the propagator orthogonal with array manifold vector and then use the orthogonal projection of joint propagator to pair the space-time parameters.According to the uniform linear array between adjacent elements phase rotation invariant features, calculation of space rotation operator and delay rotation operator to estimate parameter information of space and time delay, respectively, this method does not need spectrum peak searching can effectively estimation the central DOA and central time-delay. Compare with the maximum likelihood criterion, spectral estimation and joint estimation of subspace space-time distributed multipath signals parameter, theimprovements subspace decomposition method proposed in this thesis can effectively avoid the covariance matrix eigenvalue decomposition and optimization problem in multi-dimensional parameter estimation, so as to reduce the algorithms complexity, and has a better algorithm performance.The thesis also analyses the sparse characteristic of space-time distributed source multipath clusters signals in the channel, proposes the coherent space-time distributed multipath clusters signals parameter joint estimation method based on sparse reconstruction, which can effectively estimate the space-time parameter information in the unknown space-time distributed multipath cluster signals angular density function and time-delay density function. When the angular and time-delay density function are known, we can use the sparse reconstruction method to estimate the angular spread and time-delay spread, and it has high estimation accuracy, good resolution and insensitive of the space-time signals distribution features.