Estimation Of Signal Parameter In Nonstationary Environments And Colored Noise

Estimation of signal parameters is an important research area of signal processing with growing applications in engineering and intensive research in theory, such as radar, sonar, communication, biomedicine, etc.In recent years,much interest focuses on the research and development of high-resolution and computationally efficient techniques based on different application background.This dissertation aims at the development of high-resolution and robust parameters estimation methods, involving direction-of-arrival (DOA), range, frequency and time-delay in nonstationary environments or colored noise.The main work can be summarized as follows:1. The problem of DOA's estimation of multiple source signals incident on a arbitrary array in the presence of both unknown spatially correlated noise and sensor errors is firstly considered.A modified ML estimation of DOA's and sensor gain errors is presented.Unlike previous work, the proposed method does not impose any structure constraints or parameterization of the signal and noise covariances.The algorithm can be carried out via the alternating projection approach.Finally, the performance of the proposed method is shown with computer simulations as well as real array data.2. In Chapter 3,we discuss the problem of DOA estimation in the presence of spatially nonstationary noise fields.An estimate of the colored noise covariance matrix is firstly given.The received data for parameter estimation is then prewhitened using the estimated noise covariance, hence, overcoming the highly biased estimates. Finally, adaptive beamforming with the modified weight is also performed.Computer simulations show that the proposed method can completely remedy beam distortion.3. A new method for DOA estimation in certain nonstationary environments is presented in Chapter 4.The maximum likelihood (ML) estimations of DOA's of multiple rapidly moving sources is derived and the theoretical variance of angle estimation and the corresponding Cramer-Rao lower bound (CRLB) are also given.Its simulations show that this parametric technique is able to resolve closely spaced sources.4. Based on fourth-order cumulant,a computationally efficient method for joint estimating both directions of arrival and ranges of near field sources with known carrier frequency is firstly presented.The proposed algorithm need not any spectral peak searching and the2-D parameters are automatically paired.lt is suitable for arbitrary additive Gaussian noise environment.In the following Section, a 3-D ESPRIT method for jointly estimating of frequencies, DOA's and ranges of multiple near-field sources with unknown carrier frequencies is proposed.The parameters estimation are given by the eigenvalues of different matrices.Furthermore, its performances are confirmed by several computer simulations.5. A computationally attractive algorithm based on the propagator method is proposed for simultaneous estimation of the direction-of-arrivals and frequencies of multiple narrowband signals received at spatially separated sensors.The frequencies are found by the eigenvalues of a constructed lower dimension matrice.The arrival angles are then estimated using the associated eigenvectors as well the estimated frequencies. Simulation results are presented to demonstrate the effectiveness of the algorithm and its comparative estimation performance with two existing methods.6. The problem of joint estimating the frequencies and time-delay of multiple sinusoids received at two separated sensors is considered.The frequencies are firstly estimated using a state-space realization approach.The tune-delay is then found using a direct-form ESPRIT-like method.Finally,the performance of the proposed algorithm is demonstrated via computer simulations using sinusoidals as well as real speech data.7. In Chapter 8,a new method for estimating the Doppler and multipath time delay of the overlapping echoes for LFM pulse radar by only one period pulse signal is presented. Firstly, the Doppler frequenc...