Theoretical Framework for Estimating Target-Object Shape by Using Location-Unknown Mobile Distance Sensors

TL;DR

This paper introduces a novel theoretical framework that estimates the shape of an unknown target object using mobile distance sensors with unknown locations, without relying on position data or additional angle information.

Contribution

It presents the first method to estimate target-object shape solely from distance measurements of mobile sensors without known sensor locations.

Findings

Successfully estimates edge lengths and vertex angles of convex polygons

Achieves shape estimation without sensor position or angle of arrival data

Presents a new approach for shape estimation in unknown sensor location scenarios

Abstract

This paper proposes a theoretical framework for estimating a target-object shape, the location of which is not given, by using mobile distance sensors the locations of which are also unknown. Typically, mobile sensors are mounted on vehicles. Each sensor continuously measures the distance from it to the target object. The proposed framework does not require any positioning function, anchor-location information, or additional mechanisms to obtain side information such as angle of arrival of signal. Under the assumption of a convex polygon target object, each edge length and vertex angle and their combinations are estimated and finally the shape of the target object is estimated. To the best of our knowledge, this is the first result in which a target-object shape was estimated by using the data of distance sensors without using their locations.