Electronic Warfare Signal Processing

Electronic warfare (EW) has evolved from exploiting analog equipment flaws to an information battle. Modern autonomous threat sensors use state-of-the-art DSP algorithms to classify targets, giving them an advantage over attacking forces. This book focuses on autonomous anti-ship missiles (ASM) attacking a naval fleet and outlines the advantages of incorporating DSP algorithms into ASM, such as rapid target identification, passive decoy detection, and noise jamming mitigation.

Format: Hardback
Length: 300 pages
Publication date: 31 January 2018
Publisher: Artech House Publishers

While previous electronic warfare (EW) exploited flaws in the analogue equipment to corrupt or degrade the sensor detection or localisation capabilities, EW is now an information battle. Modern autonomous threat sensors can readily detect and locate targets by incorporating state-of-the-art high-speed digital signal processing (DSP) algorithms that focus on the classification of targets via target physical features. As a result, the autonomous threat has a significant advantage over attacking forces consisting of armoured vehicles, aircraft, or ships.

To elucidate the state of EW, this book focuses on the example of autonomous anti-ship missiles (ASM) attacking a naval fleet rather than airborne battles, thus filling a significant gap in the EW literature. It describes modern DSP algorithms that have been published by ASM development personnel from several nations, including the People's Republic of China and the Russian Federation, and outlines instances where it has been successfully used against ships.

The book elaborates on the mathematical techniques employed and the advantages of incorporating digital signal processing algorithms into the autonomous sensor. With straightforward DSP algorithms, ASM can rapidly identify and distinguish electronically generated false targets, passive decoys, chaff, and true targets. Moreover, special sensor waveforms now proactively probe the targets for enhanced feature measurements, and modern multi-channel optimal DSP readily mitigates noise jamming.

Weight: 582g
Dimension: 157 x 236 x 21 (mm)
ISBN-13: 9781630814601
Edition number: Unabridged ed