Direction-of-arrival Estimation Based On Low Precision Quantized Measurements

Generally,the problem of direction-of-arrival(DOA)estimation in antenna array systems assumes that the measurement quantization has infinite resolution,or assumes that the quantization error is insignificant and can be simply absorbed into the noise.With the emergence of large-scale antenna array systems,it is likely to be impractical due to the high hardware cost and system power consumption.Moreover,it is known that the power consumption of an analog-to-digital converter(ADC)device increases exponentially with quantization bit number.Hence,system design with low-resolution ADCs and related signal processing techniques have attracted significant research interests over the past few years.Particularly,one-bit ADCs,which are composed of simple comparators,and consuming negligible circuit power,have been widely studied in massive multiple-input multiple-output(MIMO)systems.In this context,this thesis considers the problem of DOA estimation with quantized measurements(including one-bit measurements),which is important in both communication and radar.It is shown that,under mild conditions the one-bit covariance matrix can be approximated by the sum of a scaled unquantized covariance matrix and a scaled identity matrix.Hence,the quantized covariance matrix can be directly utilized to perform DOA estimation with subspace-based techniques.In addition,an improved fixed-point continuation(FPC)reconstruction algorithm,named as FPCl₁,is developed to deal with complex-valued signals,such that it is applicable to obtain DOA estimation with one-bit measurements.Lastly,it is proposed to formulate a constrained maximum likelihood optimization problem to recover the low-rank noiseless array measurement matrix,from quantized noisy measurements.On the basis,traditional subspace-based approaches are applied to determine the DOAs.To verify the effectiveness of the proposed methods,simulations are carried out to compare the performance of the proposed and existing methods.