A novel array signal processing technique for multipath channel parameter estimation

Cataloged from PDF version of article.Many important application areas such as mobile communication, radar, sonar and remote sensing make use of array signal processing techniques. In this thesis, a new array processing technique called Cross Ambiguity Function - Direction Finding (CAF-DF) is developed. CAF-DF technique estimates direction of arrival (DOA), time delay and Doppler shift corresponding to each impinging signals onto a sensor array in an iterative manner. Starting point of each iteration is CAF computation at the output of each sensor element. Then, using incoherent integration of the computed CAFs, the strongest signal in the delay-Doppler domain is detected and based on the observed phases of the obtained peak across all the sensors, the DOA of the strongest signal is estimated. Having found the DOA, CAF of the coherently integrated sensor outputs is computed to find accurate delay and Doppler estimates for the strongest signal. Then, for each sensor in the array, a copy of the strongest signal that should be observed at that sensor is constucted and eliminated from the sensor output to start the next iteration. Iterations continue until there is no detectable peak on the incoherently integrated CAFs. The proposed technique is compared with a MUSIC based technique on synthetic signals. Moreover, performance of the algorithm is tested on real high-latitude ionospheric data where the existing approaches have limited resolution capability of the signal paths. Based on a wide range of comparisons, it is found that the proposed CAF-DF technique is a strong candidate to define the new standard on challenging array processing applications.Güldoğan, Mehmet BurakM.S

Development of new array signal processing techniques using swarm intelligence

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Ph. D.) -- Bilkent University, 2010.Includes bibliographical references leaves 144-158.In this thesis, novel array signal processing techniques are proposed for identifi- cation of multipath communication channels based on cross ambiguity function (CAF) calculation, swarm intelligence and compressed sensing (CS) theory. First technique detects the presence of multipath components by integrating CAFs of each antenna output in the array and iteratively estimates direction-of-arrivals (DOAs), time delays and Doppler shifts of a known waveform. Second technique called particle swarm optimization-cross ambiguity function (PSO-CAF) makes use of the CAF calculation to transform the received antenna array outputs to delay-Doppler domain for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components are identified by using a simple amplitude thresholding in the delay-Doppler domain. PSO is used to estimate parameters of the multipath components in each cluster. Third proposed technique combines CS theory, swarm intelligence and CAF computation. Performance of standard CS formulations based on discretization of the multipath channel parameter space degrade significantly when the actual channel parameters deviate from the assumed discrete set of values. To alleviate this “off-grid”problem, a novel technique by making use of the PSO, that can also be used in applications other than the multipath channel identification is proposed. Performances of the proposed techniques are verified both on sythetic and real data.Güldoğan, Mehmet BurakPh.D