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摘要
A neutrosophic Hough transform-based track initiation method (NHT-TI) is proposed to solve the uncertain track initiation problem in a complex surveillance environment. In the proposed method, a neutrosophic set is employed to describe the uncertain association of a measurement with different targets, which is divided into three categories, including the association with real targets, uncertain targets, and false targets, respectively. On this basis, the neutrosophic Hough transform (NHT) method is developed in the framework of the standard Hough transform (HT) method. Based on the sequential processing mode of the sensors, candidate temporary tracks are further de fined to directly calculate the parameter points in the parameter space, which are utilized to calculate the contribution for the corresponding vote cells in the accumulation matrix by using the Gaussian membership function. Based on the scheme, the NHT method can avoid large traversal operations and reduce computation complexity of the HT method. Moreover, considering the effects of noises and clutters on track initiation, two constraint conditions related to the velocity information of moving targets and the time information of measurement sequences are introduced to suppress false tracks and reduce vote times. Finally, the real tracks can be determined by detecting the peaks of the global accumulation matrix. The performance of the proposed NHT-TI method is evaluated by using two experiments with simulated data and real data in two complex surveillance environments. The results are found to be better than those of the standard HT-based track initiation (HT-TI) method, the modified HT-TI method based on candidate temporary tracks and the improved HT-TI method in detection reliability and computational complexity.
