Measuring device, measuring method, and computer readable medium

A measuring method comprising:

• taking, as a subject sensor, each of a plurality of sensors, and calculating a detection value at a subject time about a detection item of an object by using a Kalman filter, on a basis of an observation value about the detection item of the object, the observation value being obtained by observing the object with the subject sensor at the subject time;
• taking, as a subject sensor, each of the plurality of sensors, and calculating a reliability of the detection value that is calculated on the basis of the observation value obtained with the subject sensor, by using a Kalman gain in addition to a Mahalanobis distance between the observation value and a prediction value, upon given with one of the Mahalanobis distance and the Kalman gain, as a weight to a value obtained from the other, the observation value being obtained with the subject sensor, the prediction value being a value of the detection item of the object at the subject time which is predicted at a time before the subject time, the predicted value being used in calculation of calculating the detection value on the basis of the observation value, the Kalman gain being obtained in the calculation;
• and
• selecting a detection value whose calculated reliability is high among the detection values which are calculated on the basis of the observation values obtained by the plurality of sensors.

A non-transitory computer-readable medium storing a measuring program which causes a computer to function as a measuring device that performs:

• a tracking process of taking as a subject sensor, each of a plurality of sensors, and calculating a detection value at a subject time of a detection item about an object by using a Kalman filter, on the basis of an observation value of the detection item about the object, the observation value being obtained by observing the object with the subject sensor at the subject time;
• a reliability calculation process of taking, as a subject sensor, each of the plurality of sensors, and calculating a reliability of the detection value that is calculated on the basis of the observation value obtained with the subject sensor, by using a Kalman gain in addition to a Mahalanobis distance between the observation value and a prediction value, upon given with one of the Mahalanobis distance and the Kalman gain, as a weight to a value obtained from the other, the observation value being obtained with the subject sensor, the prediction value being a value of the detection item of the object at the subject time which is predicted at a time before the subject time, the prediction value being used in calculation of calculating the detection value by the tracking process on the basis of the observation value, the Kalman gain being obtained in the calculation;
• and
• a value selection process of selecting a detection value whose reliability calculated by the reliability calculation process is high among the detection values which are calculated on the basis of the observation values obtained by the plurality of sensors.