Research On Joint DOA-Delay Estimation Methods For Distributed Signals

Joint space-time parameter estimation is an important research problem in modern wireless communication systems. It is also a main concern when smart antenna technology is used in 3G systems. In complicated communication environments the multipath broadcasting caused by reflection, diffraction or refraction always lead to intersymbol interference which is the main reason for communication quality degradation. As a result the use of joint space-time parameters estimation in mobile system can restrain multipath phenomena, increase system capability and improve communication quality. At the same time the space-time parameters is very important for other space-time processing technology. So joint space-time parameter estimation method has its theory significance and application merit.Because of dense reflection caused by buildings, roads or other reasons there is no direct path between transmitter and receiver. The Not-Line-of-Sight(NLOS) propagation may cause angle spread and delay spread in transmitting signals. So traditional point-based model is not useful anymore and may bring communication quality deterioration. So it is very important to theorize and analyze distributed signal model in both space and time and is the main concern of this dissertation. Based on existing models systematic research is done to estimate DOA(direction-of-arrival) and delay parameters jointly. Several valuable and important achievements of this thesis which bring new ideas are indicated as follows:1.The deduction of space-time distributed channel model is given by considering observation noise. The performance character versus noise is anatomized carefully. The adverse influence of noises is analyzed for some channel transform technology (eg: fourier transform and deconvolution).2.A new deconvolution and joint signal subspace acquisition method is proposed and has the advantage of noise suppression.3.The traditional TST-MUSIC(multiple signal classification) method is modified using space and time distribution function. So it can be used when channel signal is distributed.4.The concept of extract subspace is put forwarded. The space search matrix and delay search matrix are constructed by extracting rows from joint space-time signal subspace. The 2-dimension search process for distributed channel estimation is decomposed into two 1-dimension search and a pairing process by using the symmetric property of space and delay distribution.5.The rotation invariant property is analyzed by considering distributed parameters in space and delay domain. Then the condition for rotation invariant property in phase is given.6.Two close-form method are given to DOA-delay joint estimation of distributed channel signals: the extract-ESPRIT and space-time ESPRIT.7.A post treatment process based on extract-ESPRIT is proposed by which estimation error can be retrained when actual signal mismatch the supposed symmetric property.8.When several paths have same parameters in space or delay the parameter merger problem is considered thoroughly. And the possibility of estimating independent path parameters by extract-ESPRIT method is proven. For those paths which have same parameters with others, a ESPRIT-MUSIC method is given while traditional space-smoothing-based decoherence technology does not work in distribution environments.In contrast with the existing maximum likelihood method, methods in this dissertation can give more accurate estimations and use less computational complexity. Those spectra methods and subspace decomposition methods proposed are insensitive to signal distributions as well.