Spectral estimation using WRLS algorithm for multiband detection

Abstract

Signal parameter estimation in the presence of noise has been a key area of research. Many applications have benefited from advancements made in this field within the last two decades. The method proposed in the thesis introduces a new family of infinite impulse response adaptive notch filters that forms multiple notches using a second-order factorization of an all-pass transfer function. The filter sections are orthogonal to each other. The resulting notch filter requires few parameters, facilitates the formation of the desired band rejection filter response, and also leads to various useful implementations (Cascaded, Parallel, Using Filter banks). In this thesis a variation of cascade type structure is used. The algorithm proposed for adaptively estimating filter coefficients is based on WRLS method. Fast convergence along with lower bias as compared to previous algorithms is achieved. This property is particularly attractive for detection and tracking of unknown sinusoids. Computer simulations are provided to illustrate the performance of the proposed adaptive notch filters in terms of bias, speed of convergence, and tracking capability. Also simulations for detection of multiband signals is given.