Signal Design for Active Sensing and Communications

Man-made active sensing systems such as active radar and sonar have been a vital part of our civilization’s advancement in navigation, defense, meteorology, and space exploration. Modern active sensing systems rely heavily on the significant progress in the science and technology of communications made within the last century. Not surprising, the fast growing communications technology has changed each and every aspect of our everyday lives. This thesis is concerned with signal design for improving the performance of active sensing and communication systems: The target detection and estimation performance of the active sensing systems can be considerably improved by a judicious design of the probing signals. Similarly, signal design has a crucial role in the implementation and efficiency of communication systems. Signal optimization for active sensing and communications usually deals with various measures of quality. This thesis focuses on several quality measures including (i) correlation and spectral metrics, (ii) signal-to-noise ratio (SNR) and mean-square error (MSE) performance metrics, (iii) information-theoretic criteria, (iv) sparsity-related metrics, and (v) beam-pattern matching metrics. The associated problems are studied and several novel algorithms are proposed to tackle the generally difficult arising problems.