Sensor array beamforming using random channel sampling: the aggregate beamformer.
The aggregate (AGG) beamformer can provide significant savings in hardware and software cost and complexity relative to conventional beamformers while retaining equivalent directional performance. The key to achieving the savings is collecting data from array channels in a random sequence, rather than simultaneously or sequentially. This allows the AGG beamformer to convert unwanted off-beam signals into wideband noise that can then be reduced by filtering. The total sampling rate is chosen to obtain the desired residual noise level and signal bandwidth. It is independent of the number of sensors. Analog anti-alias filters normally are not required, since the Nyquist frequency is determined by the total sampling rate, not the (lower) per-channel sampling rate. Beamformer delay quantization and steering resolution are greatly improved relative to conventional beamforming without the need for data interpolation. The beamformed signal, prior to decimation filtering, is obtained without arithmetic operations on the data. Low front-end hardware-complexity makes the AGG beamformer suitable for highly integrated systems. The number of sensors in the array can be altered without re-configuring buffers or altering the sampling rate. The principles of the AGG beamformer are introduced, and simulation and experimental results demonstrate performance.