Description

The Multi-hop self-calibration algorithm allows for the translation of a set of ranges between anchors (fixed tags) into a relative coordinate system. This algorithm differs from others as it is able to manage multiple hops for node positioning. Furthermore, it can position anchors even under NLoS conditions.

Principles of Multi-hop anchor initializer

The Multi-hop self-calibration algorithm is rooted in the idea of gradually incorporating anchors, considering both the existing anchor nodes’ positions and the available ranges with a prospective anchor node. Moreover, after this first initializing stage, a secondary stage is executed where the entire topology is optimized at once. In broad terms, it involves the following procedural steps:

1. Acquire ranges between anchors
2. Determine the position of at least three anchor nodes manually
3. Select an anchor to be positioned
4. Solve the position problem
5. Repeat step 3-4 until no more anchors can be added
6. Optimize whole network at once

Advantages of Multi-hop anchor initializer

1. Reduced installation time
2. Robust results in Line-of-Sight (LoS) conditions
3. Scability
4. Detection of “good” anchors

input: Set of ranges between anchors, position of n > 2 anchors
output: Set of 2D anchor positions 

Supported languages

1. Python

Supported hardware

This algorithm is meant to be run in the cloud* or on edge devices, thus supporting any hardware capable of determining the ranges between anchors.”

^{*“In the cloud” suggests that it is not designed for deployment on embedded hardware.}