Joint Estimation For Multi-Sources And Multi-Parameters On Nonideal Assumptions In The Field Of Array Signal Processing

Array signal processing plays a very important role in modern signal processing. It can be applied to a wide areas, such as radar, sonar, mobile communications, electronic surveillance, medicinal engineering, seismology, radio astronomy, etc.. So the study on this field has attracted a lot of interests of many scholars in the last two decades. Compared with many traditional techniques, the methods based on array signal processing can improve both the accuracy and the resolution of direction finding dramatically. At the same time, those parameters, such as frequency, relative time-delay and polarization of incident signals are very important for confirming the velocity, distance and characters of targets, so the joint direction and those parameters estimation are important too. On the other hand, most array signal processing methods in common use are based on many ideal assumptions such as ideal sensor array, independent white Gauss noise environments and far-field sources, etc.. If the assumptions don't come into existence, the estimating performance would be degraded, or even invalidated. Aiming at the problem of joint estimation in nonideal conditions that are frequently met with in practical application, several effective algorithms have been presented, and verified by theoretical analysis and simulations in this dissertation. The main contents of this dissertation can be summarized as follows:1. Data model for array signal processing is discussed. Based on this model, several classical methods for direction estimating are introduced, such as MUSIC, ESPRIT and DOA matrix method. For the problem of estimating direction via array manifold matrix, a novel method is presented by means of Least Square. This LS method can be used to any sensor array with arbitrary geometry structure which satisfying the spatial sampling theorem, so it is more effective and practical than other similar algorithms.2. Profound study on the effective joint Direction of Arrival (DOA) and other parameters estimation. First, aiming at the problem of joint direction, frequency and time-delay estimation in a single pulse for sonar, radar systems, a novel method based on temporal cumulating is developed, which is more effective than the existing spatial cumulating method. Through time-delay compensating, temporal smoothing technique is expanded to process the non-stationary signal with a single pulse echo, so an effective temporal-spatial expanded DOA matrix method is presented. This method has higher estimating performance and robustness because of the temporal smoothing effect, and can be used to arbitrary geometry array. Second, based on the coherent pulse sequence signal used in pulse Doppler system, a potent pulse cumulating method for joint azimuth, elevation, Doppler frequency and relative time-delay estimating is proposed in this dissertation. This pulse cumulating method can be used to arbitrary geometry array too, and the least number of pulses it need could be two. Different from those single pulse methods, the input information of pulse cumulating method will increase with the number of pulses, so its performance improvement will be more notable. Third, from the point of view of electronic surveillance, an effective temporal smoothing DOA matrix method is presented for joint azimuth, elevation, carrier frequency and polarization estimating. Compared with those existing method, this novel algorithm can be used to any sensor array, all estimates are automatically paired in calculation process, and more targets can be dealt with at the same time. Theoretic analysis and...