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Signal detection and bearing estimation are rich research areas with applications in sonar, military surveillance, navigation and search and rescue. For the case of a single sinusoid in additive white Gaussian noise, with all parameters unknown, the periodogram is the maximum likelihood estimator. Additionally, the periodogram is a non-parametric technique, providing good parameter estimation under low signal to noise conditions. When multiple sinusoids are present, high resolution techniques such as Auto-Regressive Moving Average (ARMA) and Multiple Signal Classification (MUSIC) provide accurate parameter estimates. However, when the sinusoids are weak, these parametric models produce large estimation errors. When the minimum frequency separation of the sinusoids exceeds four FFT bins and appropriate filtering is employed, the single sinusoid parameter estimation bounds of the periodogram can be applied to the multiple sinusoid case. In this thesis, a periodogram based architecture is developed, providing sinusoidal detection and bearing estimation for multiple weak sinusoids with a circular antenna array. Theoretical performance bounds are derived and compared against simulation results.

The detection and direction finding of multiple weak sinusoidal signals with a circular antenna array