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Acta Armamentarii ›› 2014, Vol. 35 ›› Issue (8): 1193-1199.doi: 10.3969/j.issn.1000-1093.2014.08.009

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Analysis of LFM Signals and Improvement of IFM System

WANG Hong-xun1,2, WANG Shi-yan2,3, WANG Xing2, WANG Hong-wei2   

  1. (1.School of Automation, Northwestern Polytechnical University, Xi’an 710072, Shaanxi, China;2.Aeronautical and Astronautical Engineering College, the Air Force Engineering University, Xi’an 710038, Shaanxi, China;3.32th Unit, 93286th Air Forces, Shenyang 110141, Liaoning, China)
  • Received:2013-06-18 Revised:2013-06-18 Online:2014-11-03
  • Contact: WANG Hong-xun E-mail:whxwhxwhx@126.com

Abstract:

Frequency is one of the key features of radar signals, which is extracted in real-time by an instantaneous frequency measurement (IFM) system in electronic warfare receivers used for RWR/ESM. Linear frequency modulation (LFM) signal is an important signal type and used widely in radar, and its frequency characteristics could not be detected by traditional IFM system. A novel technique is proposed based on improved IFM system for LFM signal feature detection, and a mathematical model of LFM signal passing through IFM system is established based on the operating principle of IFM system. The frequency resolving capacity and the minimum detectable frequency modulation slope are discussed. In the improved IFM system, a phasing detector signal is used as the effective indicating signal of sampling to extract the time of arrival (TOA) and pulse width (PW) features. The analog-digital converters (ADC) instead of polarity quantizer of traditional IFM system are used to sample continuously the outputs of the orthogonal channels. The fuzzy clearness and linear regression algorithms are used for noise smoothing and evaluating the carrier frequency and the frequency modulation slope of LFM signal. Simulation results show that the improved IFM system could extract the LFM signal features in an LFM pulse with higher accuracy, and retains the advantages of original IFM system.

Key words: radar engineering, instantaneous frequency measurement, linear frequency modulation, fuzzy clearness, linear regression

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