Waveform Design and Diversity for Advanced Space-Time Adaptive Processing and Multiple Input Multiple Output Systems

Abstract : Waveform diversity refers to the adaptivity of the radar waveform to dynamically optimize the radar performance for the particular scenario and tasks. It may also exploit adaptivity in other domains, including the antenna radiation pattern (both on transmit and receive), time domain, frequency domain, coding domain, and polarization domain. As this definition indicates, the term waveform diversity does not refer to a tangible object, but to a remote sensing paradigm. The basic elements of the paradigm are: measurement diversity, knowledge-aided processing and design, and transmitter adaptivity. The waveform diversity paradigm arose from the insatiable demands for remote sensing performance that are always present in military applications, and the application of waveform diversity has led to many interesting and promising remote sensing concepts. In this report we focus on some challenging problems concerning waveform design and diversity and propose innovative solutions. Specifically, in Chapter 1, we consider the problem of waveform design for radar sensors that operate in a noncooperative network. In Chapter 2, we deal with the problem of Pareto-optimal waveform design in the presence of colored Gaussian noise, under a similarity and an energy constraint. In Chapter 3, we consider the problem of knowledge-aided transmit signal and receive filter design for point like target in signal-dependent clutter. In Chapter 4, a network of radars sharing the same frequency band, and using properly coded waveforms to improve features attractive from the radar point of view is considered. In Chapter 5, we deal with the design of radar receive filters jointly optimized with respect to sidelobe energy and sidelobe peaks via Pareto-optimal theory. Finally, in Chapter 6, we consider the problem of cognitive transmit signal and receive filter design for a point-like target embedded in a high reverberating environment.

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