دانلود کتاب پردازش سیگنال رادار مبتنی بر نظریه اطلاعات

The roots of information theory can be traced back 100 years to the early works of Fisher [1], Nyquist [2], Hartley [3], and others. In [1], Fisher laid down a cornerstone by defining statistical information as the reciprocal of the variance of a statistical sample. This fundamental concept was later independently derived by Cramér and Rao, who utilized it to establish the lower bound on parameter estimation variance [4, 5]. Therefore, information theory has been naturally closely related to signal processing from the beginning. AfterWorldWar II, both disciplines of information theory and signal processing witnessed remarkable advancements. In 1948, Shannon published his groundbreaking article, “A mathematical theory of communication” [6], which served as a lodestar for the burgeoning discipline of information theory. In the same year, the Institute of Radio Engineers (IRE), the predecessor of the Institute of Electrical and Electronics Engineers (IEEE), inaugurated its first society, the Signal Processing Society. This historical coincidence further symbolized the close relationship between information theory and signal processing. Information theory originally emerged to explore the communication of messages. Its core principles include quantification of information, source coding, and channel coding. Shannon’s contributions fostered a vibrant community of scholars, leading to the establishment of the IEEE Information Theory Society in 1951. His legacy continues to influence the fields of communications, information theory, and signal processing. The earlier works of Woodward and Davies in the early 1950s [7, 8] marked the beginning of information-theoretic signal processing for radar applications. However, unlike communication systems, which aim to extract information from received signals in a cooperative framework, radar systems operate in noncooperative environments, seeking information about unknown targets, such as their range, velocity, and angle. This inherent disparity in understanding of information has resulted in a notable lag in the development of information-theoretic processing for radar systems compared with the communication counterparts. Information theory experienced a resurgence within the radar signal processing community following a period of stagnation spanning over three decades. A key turning point was the publication of Bell’s PhD dissertation in 1988 [9], wherein mutual information was used for the first time as an optimization criterion to design radar waveforms that maximize the target information extracted from the received measurements. Since then, information theory has witnessed a renaissance in radar signal processing, especially in the era of multiple-input multiple-output (MIMO) radar. In 2005, Guo et al. [10] provided further insights into the theoretical connection between mutual information in information theory and minimum mean square error (MMSE) in estimation theory. Nowadays, information-theoretic criteria, including Fisher information, Shannon entropy, mutual information, and Kullback–Leibler divergence (also known as relative entropy), have become the foundation of adaptive radar systems and found great success in solving various radar signal processing problems. This book provides a comprehensive introduction to information-theoretic criteria, methods, and applications in radar signal processing with a focus on the latest theoretical and practical advances in selected important topics. This book is intended not only for radar signal processing researchers, but also for postgraduate and PhD students, researchers, and engineers working on a broad spectrum of signal processing and its applications, including but not limited to radar systems. The readers are assumed to have some background in linear algebra, probability and statistics, compressive sensing, detection and estimation, control and optimization, information theory, as well as radar systems. The book contains fourteen self-contained chapters, each focusing on a specific topic. These chapters, contributed by leading experts fromacademia, industry, and government, can be broadly categorized into six areas: target detection (Chapters 1–3), parameter estimation (Chapters 4 and 5), radar imaging (Chapters 6 and 7), target tracking (Chapters 8–10), resource management (Chapters 11 and 12), and performance bound analysis (Chapters 13 and 14).