Robust Techniques for Acquisition and Processing of PH, PH/DS and Conventional Communications Signals

An SBIR project is proposed to apply optimal detection and estimation theory to acquisition (detection/classification), copy, and localization (DF) of frequency agile, hybrid FH/DS, and conventional telecommunications signals. A two-stage baseline system is proposed to accomplish this, consisting of a multisensor processor front-end, which employs dominant-mode prediction (DMP) and polychannel DMP (PC-DMP) to detect, copy, and localize emitters on the basis of their variation in time-frequency support (temporal burstiness and/or bandwidth extent); and a signel-sensor processor back-end, which employs log-likelihood functions (LLFs) and per-survivor-processing (PSP) algorithms to classify and demodulate the dehopped/downconverted emitters provided by the processor front-end. Both stages provide optimal (GLRT) statistics for detection and classification of the emitter waveforms, and provide optimal (ML) estimates of the emitter waveforms under appropriate modelling conditions. In addition, the baseline processor is compatible with channelized digital reconnaissance systems under current development, such as the TACJAM A system, in that they can operate against emitters with bandwidths larger than the frequency channelization of the reconnaissance system, even if that system employs undersampled frequency channelizers that do not allow complete regeneration of the emitter time series