A more realistic error distance calculation for indoor positioning systems accuracy evaluation

The accuracy of indoor positioning systems is commonly computed as a metric based on the Euclidean distance from estimated locations to actual locations. This paper suggests that positioning error distances should be computed as the lengths of the paths that a person may follow when going from wrongly estimated positions to the real positions. The paper proposes a method that calculates the paths from floor plan and obstacles information using the visibility graphs and offsetting techniques, which are commonly used in robotics and CAD/CAM for navigation and manufacturing, respectively. Demonstration of the proposed method was done using a WiFi fingerprinting method based on kNN for pedestrian navigation. Comparisons between our proposed distance and the simple Euclidean distance have shown that the error distances are underestimated and that the differences between the two distances cannot be accurately represented by a fixed quantity in the context of an Indoor Positioning System (IPS) deployed in a library building. We consider that our proposed positioning error distance is more in line with the subjective error perceived by IPS users.