In the vast and demanding field of radar engineering, where theory must constantly bow to the practical constraints of hardware, noise, and the elusive nature of targets, few texts achieve the delicate balance between mathematical rigor and applied insight. Radar Signals: An Introduction to Theory and Application , part of the esteemed Artech House Radar Library, stands as a landmark contribution that has educated generations of engineers. Rather than treating radar signals as mere byproducts of hardware, the book elevates them to their rightful place: the very essence of radar system design. Through a systematic exploration of waveform design, ambiguity functions, and matched filtering, the text provides not just a toolkit but a fundamental philosophy for understanding how radar “sees” the world.
The central thesis of the book is that the transmitted signal is the radar’s primary degree of freedom. While antenna design and receiver sensitivity are critical, the waveform determines fundamental performance limits in range resolution, Doppler sensitivity, and interference rejection. The text opens by grounding the reader in the necessary mathematical foundations—linear systems, modulation theory, and statistical signal processing—before launching into the core of the matter: the ambiguity function. This two-dimensional representation of a waveform’s response to range and Doppler shifts is presented not as an abstract curiosity but as a design blueprint. The book meticulously demonstrates how a simple rectangular pulse offers excellent range resolution only at the expense of poor Doppler discrimination, while a continuous wave (CW) tone provides the opposite. The genius of the text lies in showing how more complex signals, such as linear frequency modulated (LFM) chirps and phase-coded sequences (Barker, Frank, and Golomb codes), can shape the ambiguity function to approximate the ideal “thumbtack” response—high resolution in both dimensions without ambiguous sidelobes. In the vast and demanding field of radar
One of the most practically valuable sections of the book addresses the challenge of pulse compression. The authors explain, with clarity and mathematical depth, how long-duration, low-peak-power signals can be processed to achieve the range resolution of a very short pulse. The matched filter, derived from the Schwarz inequality, is introduced as the optimal linear processor for detecting a known signal in white noise. But the text does not stop at theory; it dives into the engineering trade-offs inherent in implementing pulse compression, such as the trade-off between time-bandwidth product, range sidelobe levels, and Doppler tolerance. The discussion of weighting functions (Taylor, Hamming, and Kaiser windows) to suppress range sidelobes is particularly illuminating, showing how a small loss in signal-to-noise ratio (SNR) can yield dramatic improvements in dynamic range and target masking. The text opens by grounding the reader in