Maneuver Classification of a Moving Vehicle with Six Degrees of Freedom Using Logistic Regression Technique

Abstract

This paper presents a novel on line algorithm for maneuver classification of a moving vehicle with six degrees of freedom, using on-board MEMS IMU’s data (three accelerometers and three rate gyros). The classification is either discrete (i.e. high, low or no maneuver), or continuous (a value that reflects the intensity of the maneuver). It should be mentioned that there is no explicit solution for this problem in any research paper previously published, due to the inability to find a direct mathematical model capable of characterizing this problem, despite its importance and its impact in improving the functioning of navigation systems. The proposed algorithm is based on a machine learning technique called logistic regression, which is a discriminative probabilistic classification model. Computer simulations, using MEMS IMU’s data taken from real experiments of an UAV, showed the effectiveness of the proposed algorithm, taking into account the sampling time, and the suitability for a wide spectrum of applications.