Joint Angle-Frequency Estimation for Multiple Signals with Circular Arrays

Abstract

In electronic warfare information about radio signals is gathered. Parameters as the direction-of-arrival (DOA) and the frequency can be estimated from sampled data received on antenna arrays. The objective of this thesis is to investigate the use of circular arrays for joint angle-frequency estimation (JAFE). A 1-D (azimuth and frequency) and 2-D (azimuth, elevation and frequency) JAFE algorithm is presented. Both algorithms use phase-mode excitation and ESPRIT. The 1-D algorithm with spatial smoothing is introduced. With this algorithm it is possible to estimate signals with similar frequencies, when the elevation is the same and known for all signals of interest. Simulations demonstrate that when two signals are coherent and a spatial smoothing factor of two or higher is applied the algorithm is able to estimate the azimuth correctly. It is also demonstrated that when two signals have the same DOA a temporal smoothing factor of two is necessary and that more temporal smoothing reduces the standard deviation of the azimuth estimation. It is shown that the phase-mode excitation technique introduces a systematic error that is considerably high for few antenna elements and an even number of elements. It is demonstrated that interpolation can reduce this error in case a UCA of 5 elements, but not for a UCA of an even number of 12 elements. The sample rate used for sampling can be adjusted to the Nyquist rate or higher. Simulations demonstrate that a little bit oversampling reduces the RMSE (Root Mean Square Error) of the azimuth, elevation and frequency. It shows that after a certain point oversampling increases the RMSE error of the elevation and especially the frequency estimation. An ESPRIT-based algorithm for joint angle-frequency-delay estimation is introduced. For the delay estimation, using a matched filter approach with ESPRIT, it is possible to estimate the delay correctly for a SNR above 40 dB only, since it is very sensitive to imperfections in the signal separation.