ATTITUDE MEASUREMENT OF 3-D OBJECT USING BACK-PROPAGATION NEURAL NETWORK

For this topic we try to find a general and practical method. Due to its strong capabilities of self-organizing, self-learning and fast parallel processing, neural network is expected to solve this problem. Afterconsidering the main disadvantages in back-propagation neural network: long-training and local-minimum problems, we propose an architecture of hierachically connected network. As a result, the trainingbecomes much faster and the local-minimum much scarcely appears. Some satisfactory results in the attitude measurement of aircraft have been obtained.