Title :
Gradient algorithm for quantization levels in distributed detection systems
Author :
Helstrom, Carl W.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Abstract :
An iterative gradient algorithm is presented for determining the quantization levels in each of a number of independent sensors so arranged as to pick up a common signal field. The system is to satisfy the Neyman-Pearson criterion that the probability of detection be maximum for a preassigned false-alarm probability. In general a number of local maxima exist, and the proposed method enables efficient search for these by starting from a variety of initial trial values.<>
Keywords :
iterative methods; probability; quantisation (signal); signal detection; Neyman-Pearson criterion; distributed detection systems; initial trial values; iterative gradient algorithm; preassigned false-alarm probability; probability of detection; quantization levels; search; Electromagnetic fields; Iterative algorithms; Probability density function; Quantization; Sensor fusion; Sensor systems; Statistical distributions; Statistics;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
