Adaptive processing using real weights based on a direct data domain least squares approach

In traditional, adaptive signal processing algorithms one change both the amplitude and phase of the weight vectors associated with an array at each of the antenna elements. The use of complex weights offers greater control over the array response at the expense of system complexity. However, it is easier if one requires only amplitude variation with a fixed phase for all the weight vectors associated with all the antenna elements. Because one uses only real arithmetic operations to find the amplitude of the weights connected to the antenna, the computational complexity is reduced considerably. Hence, this paper addresses the use of real weights in an adaptive system. In this paper we describe a new direct data domain least squares (D³LS) method using real weights, which utilizes only a single snapshot of the data for adaptive processing. This technique may be useful for real time implementation of the D³LS method on a chip.