Optimal adaptive processing for domain factorised element-digitised array radar

For large phased array radar, digitisation and adaptive beamforming are usually performed at the subarray level. The number of subarrays is usually much smaller than the number of array elements thus reducing the number of available adaptive degrees of freedom (DOF). For an element digitised array radar (EDAR), a subarray technique can also be employed to reduce the number of adaptive channels in order to reduce the adaptive processing load. However, EDAR allows greater flexibility in the choice of adaptive channels from the array elements, thus allowing alternative DOF reduction techniques to be investigated. An adaptive technique using a convolution approach, namely `range-dependent gain adaptation using domain factorisation´ (RDGA-DF), has been shown to give significant advantages over subarray level adaptive beamforming when cancelling strong sidelobe clutter in the airborne environment. A new implementation of the RDGA-DF algorithm is developed to perform adaptive processing on a domain factorised array. This algorithm, called the `full aperture convolution technique´ (FACT), is derived directly from the optimal Wiener filter solution. The performance advantages of FACT over RDGA-DF are demonstrated by simulation