Robust improvement of target resolution in azimuth and range

This thesis addresses the development of a robust processing technique aimed at resolving and unmasking targets, in range and azimuth, embedded in the received signal of a single and monostatic rotating surveillance radar. The reason for the need of such technique is twofold. Firstly, there are several relevant applications, from collision avoidance between small boats and large ships to distinction of individual humans within groups of people, that require a fine separation between targets in range and azimuth. Secondly, it is necessary for the technique to be robust by counteracting deterioration of the unmasking and resolving capability when the received signal model underlying the processing technique does not perfectly correspond to the actual received signal, and correctly operate in realistic conditions of constructable electronics and targets. The novelties comprised in this thesis include the following points. An increased robustness of the method is achieved by means of distortion estimation to allow mitigating for impairments, such as the ones due to a discrepancy between the reference stored in the processing and the echoes in the received signal. The scheme is extended to unmask and resolve close targets in azimuth. Analytical derivations are used to characterize the output of the processing scheme in the multiple target cases. An investigation is made of the effects on the scheme due to misaligned targets, moving targets, saturation on receive, bandwidthlimited signals. Validation through experimental proof of the resolving and unmasking capabilities of the scheme is obtained with experiments ranging from synthesized data based on a recorded antenna pattern, to a complete radar transceiver chain experiments with propagation in air and static and simulated targets, to data recorded from a commercial radar illuminating real moving targets. The method used in this thesis work comprises the successive steps of mathematical development of the processing scheme, simulation analysis, and validation through experiments. Following the introduction, in Ch. 1, which gives an overview of the thesis work motivation, objectives, method, and outline, Ch. 2 places the technique developed in this thesis in the context of other existing techniques for target resolution and unmasking. In Ch. 3 the processing scheme is described, preceded by an explanation of the statistical approach in which it is placed. The robust processing technique is iterative and consists of two elements: a filter estimation scheme and distortion estimation scheme, both obtained from a linear minimum mean square error cost function computed on the processed received signal. The pre-processing includes Doppler-processing in order to cope with targets with nonzero radial speed, and to allow separating targets with same Doppler but different range or azimuth location. A description of the mathematics underlying the processing scheme is presented in Ch. 3. And it is analyzed in detail in Ch. 4 in terms of the filter output in the different cases of absence of targets, single target, and two targets, leading to the generalization to multiple targets. Other cases addressed are the presence of distortion and of a noisy replica stored in the processing. In this chapter the signal-to-noise ratio at the output of the filter is compared to the one at the output of the matched filter. After introducing the context and the technique, Ch. 5 gives an overview of some simulation results. These span: from the case of perfect matching between the received signal and its model, including a perfectly correct reference stored in the processing; to a comparison with the output of the CLEAN algorithm, for the multiple target cases with and without oversampling of the received signal and reference; to aspects that can occur in reality, such as a misaligned target with respect to the sampling in the radar processing, moving targets causing a Doppler shift, missing samples in the received signal, saturation on receive, and the case when the reference stored in the receiver is not correct, as an example of imperfect matching of the received signal and its model. In theses simulations it is possible to see the unmasking and resolving capabilities of the technique. In particular when the reference stored is not perfectly matching the echoes in the received signal the distortion compensation still allows to solve and unmask the targets. The measurement trials and results, in Ch. 6 and 7, constitute the validation part of this thesis. These are arranged in successive steps: starting from synthesized received signals based on actually recorded antenna pattern in amplitude and phase; passing on to measurements in an anechoic chamber with propagation in air at radio frequency, with a signal generated from test equipment and a downconverter and oscilloscope on receive; to data recorded from a commercial radar illuminating actual moving targets during trials. These experiments show how the technique does not deteriorate in the case of operation with actual hardware, such as characterized by a limited bandwidth, in the case of targets that do not occur perfectly centered in the radar bin, in the case of targets affected by Doppler shift. If the reference stored in the processing is not perfectly equal to the echoes present in the received signal the distortion compensation allows to avoid deterioration of the filter output. Finally, Ch. 8 includes a summary of the thesis, with particular emphasis on the aspects of novelty and an outlook on future research. The recommendations given include considerations for the application of the technique to commercial radar.