Adaptive beamforming using improved decision tree model for BPSK communication system

In Multi-sensor data fusion technology, array processing is an area of signal processing. A sensor array captures spatially propagating signals arriving from a certain direction and processes them to obtain useful information. To this end, it is intended to linearly combine the signals from all the sensors with coefficients in a manner, so as to estimate transmitted data radiating from a specific direction. In beamforming, an array processor steers a beam to a certain direction by computing a properly weighted sum of the individual sensor signals just as an finite impulse response (FIR) filter generates an output (at a frequency of interest) that is the weighted sum of time samples. Current methods to calculate the weight coefficients are complex. Designed model is a simple and effective weight coefficient calculation method based on improved decision tree model where it combines the best features of neural network and decision trees. This technique is based on the optimum beamformer and makes it robust to an faulty estimate of the Direction Of Arrival (DOA) even when powerful interferences are within the uncertainty range of the desired source. The proposed algorithm is the product of an effort to provide more efficient procedure for real time implementation of array signal processing and is useful for wireless communication with Binary Phase Shift Keying signalling.