Finding Algorithm Described In Array-based Signal Synthesis And Sparse Signal

Array signal processing is a very active area of technology currently, and the direction-of-arrival (DOA) estimation problem is an important research area of array signal processing. As the rapid development of signal processing technology, how to improve the performance of the DOA estimation has become the current research focuses. In practice, the general ideal conditions required by the algorithm is always difficult to meet. Signals faces complex electromagnetism environments with a variety of interferences and noises, and the frequency range of signal is becoming wider, so the good performance DOA estimate becomes more and more difficult. The main contents of this paper are as follows:(1) Proper processing signals from the antenna to improve the SNR of received signal: With maximum antenna apertures and lower receiver noise temperatures pushed to their limits, one remaining method for improving the effective SNR is to combine the signals from several antennas. This is referred to as array signal combining. The output of an array is a weighted sum of the input signals applied to the combiner, where each of these input signals comes from the various antennas in the array, and then give an improvement in SNR. The complex weights providing corrections for both the amplitude and phase of the signals can be derived in a number of ways. Theoretical analysis and computer simulations show that the array signal combining can give an improvement in SNR.(2) Searching for a good performance DOA estimation algorithm: the algorithm based upon a sparse representation of sensor measurements with an overcomplete basis composed of samples from the array manifold, that is the l1 ? SVD method. It enforces the sparsity by imposing penalties based on the l1 -norm, uses the singular value decomposition (SVD) of the data matrix to summarize multiple time samples. This method leads to an optimization problem, it solves efficiently in a second-order cone (SOC) programming by using the combinatorial optimization database SeDuMi. Theoretical analysis and computer simulations show that the algorithm can effectively improve the performance of DOA estimation under low SNR and coherent signal conditions, and also combined with array signal combining algorithm to improve the performance of DOA estimation under low SNR conditions.(3) The DOA estimation of non-uniform array: As the aperture of array will affect the accuracy of measurement directly, in order not to change the aperture of array after the array signal combining, so the uniform array will become to a non-uniform array. First introduces the reasons of ambiguities, and then introduces three kinds of irregular array to resolve the ambiguities. Theoretical analysis and computer simulations show that the algorithm can effectively resolve the ambiguities. Using the Simple method to complete the array signal combining, through the computer simulations show that the Simple method can give an improvement in SNR.