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Frequency-Invariant (FI) beamformer is a type of beamformer that has flat spatial response over a wide range of frequency. In most of the algorithms presented today, this FI characteristic is true for all angles including both main lobe and side lobe. In this paper, a novel uniform circular broadband beamformer with frequency-invariant characteristic is proposed. It attempts to optimize the FI beampattern solely for the main lobe where the signal of interest is from and relax the FI requirement on the side lobe. As a result, the beamformer achieves better FI response for the desired region and it is completed in one single step. In order to achieve this goal, a new objective function with a quadratic constraint is designed. In addition, the constraint function allows the FI character to be accurately controlled over the specified bandwidth at the expense of other parts of the spectrum which are not of concern to the designer. State-of-the-art optimization method such as Second Order Cone Programming (SOCP) is used to solve this complex optimization problem with high efficiency and accuracy. Simulation result shows that the proposed beamformer can obtain better performance in achieving FI for the main lobe.I.

The knowledge of Doppler spread is very important in many channel estimation (tracking) algorithms for flat fading channels. Recently, Doppler spread estimators based on the profile of the power spectral density (psd) have been published. They make use of the fact that there is an abrupt change in the psd around the maximum Doppler frequency. However, this assumption is invalid in low signal-to-noise ratios (SNRs). In this paper, we introduce an iterative Kalman autoregressive (IKAR) estimator which overcomes this drawback. In doing so, we also study the excellent detection properties of the IKAR detector and demonstrate its superiority over some of the conventional detectors. The IKAR estimator performance is studied for two low SNR scenarios.