研究目的
To propose a novel adaptive wideband beamforming method that overcomes the constraint of conventional broadband beamforming requiring the desired signal to be incident from the broadside, by utilizing digital delay filters and LMS based space-time adaptive filtering algorithm.
研究成果
The proposed adaptive wideband beamforming methodology based on digital delay filter and LMS algorithm effectively overcomes the constraint of conventional broadband beamforming, allowing the signal of interest to be treated as if it arrived from the broadside. It achieves broadband interference suppression, high resolution to steer the main beam in the direction of desired signal, and nulls the interferences, with significantly reduced computational complexity compared to DMI algorithm.
研究不足
The proposed methodology requires the design of FIR filters for fractional delay compensation, which, although not high in order, adds to the hardware complexity. The choice of optimal window method for the FIR filter design is complicated.
1：Experimental Design and Method Selection:
The methodology involves the use of digital delay filters to compensate the delay of receiving data, making the signal of interest appear as if it arrived from the broadside. LMS based space-time adaptive filtering algorithm is then applied for beamforming.
2：Sample Selection and Data Sources:
A uniform linear array with N sensors is considered, with the first array sensor as the reference. Far-field signal model is assumed with desired and interference signals being non-coherent wideband signals.
3：List of Experimental Equipment and Materials:
MATLAB simulations are conducted using a uniform linear array composed of 8 elements with 7-order tap delay of digital filter.
4：Experimental Procedures and Operational Workflow:
The process involves compensating the delay of the antenna received signal via digital time delay filters, calculating the tap weight vector through LMS algorithm, and applying delay processing to the optimum weight vector.
5：Data Analysis Methods:
The computational complexity of the proposed algorithm is compared with that of the DMI algorithm based on a count of the total number of complex multiplications and complex additions involved.
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