Enemy integrated air defense systems (IADS) using low probability of intercept (LPI) emitters can cause significant problems for suppression of enemy air defense (SEAD) techniques. New threat emitter configurations using low-power random noise modulation have a significant processing gain unavailable to non-cooperative intercept receivers. Consequently, the detection of these emitters can not be accomplished with conventional intercept receiver detection methods. This thesis examines the use of time-frequency, bi-frequency signal detection techniques to identify the parameters of the four types of continuous waveform noise radar recently reported. These include: (a) random noise, (b) noise plus frequency modulation continuous wave (FMCW), (c) noise FMCW plus sine and (d) random binary phase modulation. Quadrature mirror filtering for wavelet decomposition is used to investigate the four types of noise signals in order to extract the signal parameters. The FFT accumulation method for estimating the spectral correlation density function is also used to examine the cyclostationary bi-frequency properties of the waveforms. In addition, the periodic autocorrelation function and periodic ambiguity function are studied to determine the waveform properties in the delay- Doppler offset domain. Results show that non-cooperative intercept receivers can increase their processing gain using these types of signal processing techniques providing a more efficient response time to the threat.

http://archive.org/details/timefrequencybif109452636