Maximum-likelihood estimators for the time and frequency differences of arrival of cyclostationary digital communications signals

Advanced techniques have been employed for decades in the location of emitted communications signals. The use of cyclostationary maximum-likelihood estimators (MLE) applied to time different of arrival (TDOA) and frequency difference of arrival (FDOA) techniques for target emitter location is a newly developed approach. This dissertation provides an introduction to traditional TDOA and FDOA methods and the underlying cyclostationary theory of pseudo-random signals. A survey of current cyclostationary TDOA and FDOA methods, the description of new maximum likelihood estimators (MLEs) and descriptions of Monte Carlo simulations follow this. By comparing performance results to those of the Complex Ambiguity Function (CAF), it is shown that the new MLE(s) outperform the CAF in nearly all cases. Also, by comparison to the Cramer-Rao lower bound, the new MLE(s) provide a hint of the ultimate power of cyclostationary techniques over stationary techniques, exceeding this stationary theoretical lower bound on performance in many cases. Finally, the new MLE(s) perform comparably in the measurement of TDOA to those cyclostationary algorithms previously derived, when adjustments are made for the different signal environments used in the heritage work.