Simulated Annealing Design of Time-Domain Coding for FMCW Radar Coexistence
(2024) EITM01 20232Department of Electrical and Information Technology
- Abstract
- For range, velocity and angle measurements, radar is a common technique to use, be it in the automotive industry, defense industry, or for medical purposes. Radars can achieve accurate measurements while also being unaffected by weather conditions such as rain, fog, or backlight. In many use cases, it might be necessary to use several radar units, which in turn allows for the possibility of causing mutual coherent interference. To avoid this interference, time division multiplexing can be utilized, which degrades the rate of the Coherent Processing Intervals (CPIs). Another possible solution could be to shorten the CPIs to avoid interference while preserving the CPI rate, but this would worsen the velocity resolution. In this work, sparse... (More)
- For range, velocity and angle measurements, radar is a common technique to use, be it in the automotive industry, defense industry, or for medical purposes. Radars can achieve accurate measurements while also being unaffected by weather conditions such as rain, fog, or backlight. In many use cases, it might be necessary to use several radar units, which in turn allows for the possibility of causing mutual coherent interference. To avoid this interference, time division multiplexing can be utilized, which degrades the rate of the Coherent Processing Intervals (CPIs). Another possible solution could be to shorten the CPIs to avoid interference while preserving the CPI rate, but this would worsen the velocity resolution. In this work, sparse CPIs that can be transmitted simultaneously without interfering have been designed. This allows for simultaneous transmission without decreasing the CPI rate or degrading the velocity resolution. To preserve as much as possible of the radar units' measurement qualities, finding these sparse CPIs were posed as an optimization problem where the spectral properties of the CPIs were also taken into account. To solve this non-linear and combinatorial optimization problem the probabilistic algorithm Simulated Annealing was used. Naive CPIs which would not cause interference were used to compare with the CPIs resulting from the optimization. The algorithm successfully finds CPIs that would not cause interference and possess better spectral qualities than the naive CPIs. The optimal CPIs were also compared with results generated using the coprime method used in the related field of designing sparse arrays. However, whether the solutions found are truly optimal is unknown, since the method approximated the optimal solution rather than finding the exact optimal CPI. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9166760
- author
- Hillbom, Vilgot LU
- supervisor
- organization
- course
- EITM01 20232
- year
- 2024
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Radar, FMCW, Interference, Simulated Annealing, Coexistence
- report number
- LU/LTH-EIT 2024-982
- language
- English
- id
- 9166760
- date added to LUP
- 2024-06-24 13:31:33
- date last changed
- 2024-06-24 13:31:33
@misc{9166760,
abstract = {{For range, velocity and angle measurements, radar is a common technique to use, be it in the automotive industry, defense industry, or for medical purposes. Radars can achieve accurate measurements while also being unaffected by weather conditions such as rain, fog, or backlight. In many use cases, it might be necessary to use several radar units, which in turn allows for the possibility of causing mutual coherent interference. To avoid this interference, time division multiplexing can be utilized, which degrades the rate of the Coherent Processing Intervals (CPIs). Another possible solution could be to shorten the CPIs to avoid interference while preserving the CPI rate, but this would worsen the velocity resolution. In this work, sparse CPIs that can be transmitted simultaneously without interfering have been designed. This allows for simultaneous transmission without decreasing the CPI rate or degrading the velocity resolution. To preserve as much as possible of the radar units' measurement qualities, finding these sparse CPIs were posed as an optimization problem where the spectral properties of the CPIs were also taken into account. To solve this non-linear and combinatorial optimization problem the probabilistic algorithm Simulated Annealing was used. Naive CPIs which would not cause interference were used to compare with the CPIs resulting from the optimization. The algorithm successfully finds CPIs that would not cause interference and possess better spectral qualities than the naive CPIs. The optimal CPIs were also compared with results generated using the coprime method used in the related field of designing sparse arrays. However, whether the solutions found are truly optimal is unknown, since the method approximated the optimal solution rather than finding the exact optimal CPI.}},
author = {{Hillbom, Vilgot}},
language = {{eng}},
note = {{Student Paper}},
title = {{Simulated Annealing Design of Time-Domain Coding for FMCW Radar Coexistence}},
year = {{2024}},
}