Eliminating the Quantization Problem in Signal Subspace Techniques
Ioannis Dacos, A. Manikas · IEICE Transactions on Communications · 1995
When signal subspace techniques, such as MuSIC, are used to locate a number of incident signals, an exhaustive search of the array manifold has to be carried out. This search involves the evaluation of a single cost function at a number of points which form a grid, resulting in quantization-error effects. In this paper a new algorithm is put forward to overcome the quantization problem. The algorithm uses a number of cost functions, and stages, equal to the number of incident signals. At each stage a new cost function is evaluated in a small number of special directions, known as . For an -element array the characteristic characteristic points 5 points, which can be pre-calculated from the array manifold curvatures, partition the array manifold into regions. By using a simple gradient algorithm, only an small area of 5 c one of these regions is searched at each stage, demonstrating the potential benefits of the proposed approach. I. Dacos was formerly with Imperial College of Science, Technology and Medicine and is now with Hellenic Air Force Academy, Decelia, Athens, Greece. A. Manikas is with the Department of Electrical and Electronic Engineering, Imperial College of Science Technology and Medicine. Please address all correspondence to: Dr A. Manikas, Department of Electrical and Electronic Engeeniring, Imperial College of Science, Technology and Medicine, London, SW7 2BT, UK. One of the authors, I. Dacos, is indebted to the Onassis Foundation for the Research Scholarship he has been awarded.