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tdoa_localisation's Introduction

TIME DIFFERENCE OF ARRIVAL (TDOA) LOCALISATION

Time difference of arrival (TDOA) is an estimation method for target localisation. Repository contains Python3 scripts for:

  • Cramer-Rao Lower Bound for unbiased target estimation,
  • Maximum-Likelihood estimation using gradient descent,
  • Best-Linear-Unbiased estimation.

Documentation

docs/instructions.pdf contains the necessary instructions for the assignment. docs/solutions.pdf contains theory and algorithms.

Installation

Clone this repository and install the requirments using

git clone https://github.com/kamath-abhijith/TDOA_Localisation
conda create --name <env> --file requirements.txt

Run

  • data/TDOA_data.mat contains the data. See data/README_hw1 for the structure.
  • Run tdoa_ml.py to generate Figure 1(a).
  • Run tdoa_blue.py to generate Figure 1(b).
  • Run tdoa_montecarlo.py to generate Figure 2.

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tdoa_localisation's Issues

No license information in this repo.

I'm interested in comparing a number of different TDOA approaches in various environments (noise, obstructions, etc); and your repo looks like it has some of the cleaner implementations of a couple algorithms, as well as including a nice test/comparison framework. If this repo had a F/OSS license it would be convenient to plagiarize use๐Ÿ™‚ your code as a starting point rather than re-implement them.

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