Comparison and Improvement of 3D-Multilateration for Solving Simultaneous Localization of Drones and UWB Anchors

Abstract

Drone fleets have attracted a lot of attention from the research community in recent years. One of the biggest challenges in deploying such systems is localization. While GNSS localization systems can only be effective in open outdoor environments, new solutions based on radio sensors (e.g., ultra-wideband) are increasingly being used for localization in various situations and environments. However, self-localization without prior knowledge of anchor positions remains an open problem, which, for example, makes it impossible to track a moving target. In this article, we provide a comparison of different variants of gradient descent-based algorithms, with a new improved variant, for solving the localization problem using relative distance measurements and multilateration. Extensive simulation results are provided, varying the number of neighboring nodes for multilateration, algorithm initialization, and cost functions, in addition to accounting for node positioning errors and ultra-wideband sensor noise. They help set the adequate rate for fixed step descent when used and produce a damping effect in the variable step rate, which will otherwise diverge. In particular, we consider three scenarios: (i) self-localization of anchors; (ii) tracking moving targets using ultra-wideband range sensors; and (iii) simultaneously estimating unknown positions of ultra-wideband anchors and mobile agents (drones). The latter shows a great improvement in localization accuracy.

Radar-Based Millimeter-Wave Sensing for Accurate 3-D Indoor Positioning: Potentials and Challenges

“…Through the exploitation of geometric relationships between the object and these reference points, multilateration algorithms facilitate the calculation of intersecting spheres or hyperboloids, ultimately yielding the object's coordinates. In this work, 3D position estimation is done using the standard algebraic solution [35] of the 3D multilateration problem where the unknown 3D position p i = (x i , y i , z i ) T is calculated algebraically given their relative distance measurements d i,j to a set of k anchors with known coordinates denoted as P n j = (x j , y j , z j ) T . The formulation of this approach can be seen below:…”

Real-Time AI-Driven Fall Detection Method for Occupational Health and Safety

“…It should be noted that the localization algorithm was not the primary focus of this contribution; therefore, only a very rudimentary approach was used. As the published dataset also includes the raw ranges to the anchors, the research community is welcome to try different multilateration algorithms, research into which is very active [42,55].…”

UWB Sensing for UAV and Human Comparative Movement Characterization

“…Due to their high-precision and capability to sense even in non line-of-sight (NLoS), the UWB sensing systems seem be a strong alternative in this field [ 28 , 29 ]. Hence, [ 30 , 31 ] presented several signal processing approaches that can be used in collaboration with UWB sensors to detect and characterize moving targets. In [ 30 ], the authors provided a promising solution for the multiple LSS UAV localization using the gradient descent method, whereas [ 31 ] addressed the problem of identifying the respiratory movement of human targets placed on the ground.…”

“…The acquired signals are processed using non-parametric methods such as the wavelet transform and the phase diagram concept. The performance of the parametric methods used in [ 30 , 31 ] strongly relies on the choice of the input parameters, while the choice of the use of the methods proposed in this paper was based on the fact the both methods do not need any a priori information regarding the sensed environment, and only rely on the characteristics of the emitted signal, information that is available for active sensing applications. Moreover, in the case of drone movement characterization, in [ 32 ], several classical methods were used and the state-of-the-art methods performed worse than the methods proposed in this paper.…”