1. A method of collecting and constructing training location data in a positioning system, adapted for a test signal space having a plurality of beacons and a plurality of training locations, comprising: detecting at each training location the signal patterns of beacons among the plural beacons that are adjacent thereto for converting the same into signal vectors relating to each training location while integrating the signal vectors of each training location so as to calculate a feature vector for each training location; recording the coordinate of each training location and the corresponding feature vector; introducing the coordinate and the feature vector of each training location into a numerical data fitting model so as to construct a signal pattern function for each beacon representing the signal pattern distribution of each beacon in the test signal space; specifying a position to be detected and then detecting the signal patterns of beacons among the plural beacons that are adjacent and related to the detected position so as to convert the same into a comparison signal vector; constructing a discriminant function based on the comparison signal vector and the signal pattern functions of the plural beacons; and using a numerical optimization search technique to find the minimum of the discriminant function so as to define the location relating to the minimum of the discriminant function as the coordinate of the detected position in the test signal space.