Object Detection, Location and Identification at Radio Frequencies in the Near Field
Lead Research Organisation:
Keele University
Department Name: Faculty of Natural Sciences
Abstract
Recent events in the UK (eg the 2019 London Bridge Attack, in which 2 people were killed, and the Terror Related Streatham Incident, where 2 people
were stabbed) have highlighted the need for improved early stand-off detection of threats, which include knives, guns and improvised explosive devices. To be able to characterise and identify these small objects at stand-off distances in the order of 10s metres from the sensor using electromagnetic field measurements requires frequencies in the 300MHz to 12GHz range, where wave propagation effects are important. Frequencies in this range have also been traditionally been used in radar (radio detection and ranging) for large objects (eg ships, aircraft and air borne threats) over much larger distances from the sensor using far field scattering pattens. However, while radar is traditionally associated with the positioning and detection of objects in the far field, radar can also used be for the classification of objects in the near field (such as in autonomous vehicles, parking sensors, and ground penetrating radar (GPR) for finding landmines and unexploded ordnance, archaeological searches and the location of utilities for the construction industry). Furthermore, there is also considerable interest in improved object positioning given the development of autonomous vehicles by Google, Tesla, Uber and many others as well as related applications in autonomous manufacturing. In all these applications there is also considerable demand to improve the characterisation and identification of small objects that are not impeded by boundaries that can be penetrated by electromagnetic fields (eg walls, ground, clothing, smoke, fog or clouds).
This proposal is aimed at improving the characterisation, classification and identification of small objects in the near field using electromagnetic frequencies in the range 300MHz to 12GHz leading to new mathematical results, statistical computing tools for object identification and design recommendations for electromagnetic sensors. Our hypothesis is that a higher tensor description of an object combined with a probabilistic classification approach provides an effective means of identifying small objects using electromagnetic field measurements positioned away from the target, but in the near field, at wave propagation frequencies.
To test our hypothesis, we will derive new asymptotic expansions, which lead to new object characterisations in terms of new tensor descriptions. We will investigate new minimal contracted representations of objects using these tensors and understand the information about an object that can be obtained from these minimal representations. We will develop new computational tools for computing these characterisations and classifiers that build on a library of tensor coefficients to make object predictions from practical measurements.
were stabbed) have highlighted the need for improved early stand-off detection of threats, which include knives, guns and improvised explosive devices. To be able to characterise and identify these small objects at stand-off distances in the order of 10s metres from the sensor using electromagnetic field measurements requires frequencies in the 300MHz to 12GHz range, where wave propagation effects are important. Frequencies in this range have also been traditionally been used in radar (radio detection and ranging) for large objects (eg ships, aircraft and air borne threats) over much larger distances from the sensor using far field scattering pattens. However, while radar is traditionally associated with the positioning and detection of objects in the far field, radar can also used be for the classification of objects in the near field (such as in autonomous vehicles, parking sensors, and ground penetrating radar (GPR) for finding landmines and unexploded ordnance, archaeological searches and the location of utilities for the construction industry). Furthermore, there is also considerable interest in improved object positioning given the development of autonomous vehicles by Google, Tesla, Uber and many others as well as related applications in autonomous manufacturing. In all these applications there is also considerable demand to improve the characterisation and identification of small objects that are not impeded by boundaries that can be penetrated by electromagnetic fields (eg walls, ground, clothing, smoke, fog or clouds).
This proposal is aimed at improving the characterisation, classification and identification of small objects in the near field using electromagnetic frequencies in the range 300MHz to 12GHz leading to new mathematical results, statistical computing tools for object identification and design recommendations for electromagnetic sensors. Our hypothesis is that a higher tensor description of an object combined with a probabilistic classification approach provides an effective means of identifying small objects using electromagnetic field measurements positioned away from the target, but in the near field, at wave propagation frequencies.
To test our hypothesis, we will derive new asymptotic expansions, which lead to new object characterisations in terms of new tensor descriptions. We will investigate new minimal contracted representations of objects using these tensors and understand the information about an object that can be obtained from these minimal representations. We will develop new computational tools for computing these characterisations and classifiers that build on a library of tensor coefficients to make object predictions from practical measurements.
People |
ORCID iD |
Paul Ledger (Principal Investigator) |
Publications
Elgy J
(2023)
Computations and measurements of the magnetic polarizability tensor characterisation of highly conducting and magnetic objects
in Engineering Computations
Elgy J
(2023)
Reduced order model approaches for predicting the magnetic polarizability tensor for multiple parameters of interest
in Engineering with Computers
Kernot D
(2022)
Transient changes during microwave ablation simulation : a comparative shape analysis
in Biomechanics and Modeling in Mechanobiology
Ledger P
(2023)
Characterising small objects in the regime between the eddy current model and wave propagation
in European Journal of Applied Mathematics
Ledger P
(2022)
Minimal Object Characterizations Using Harmonic Generalized Polarizability Tensors and Symmetry Groups
in SIAM Journal on Applied Mathematics
Ledger P
(2022)
Properties of Generalised Magnetic Polarizability Tensors
Ledger P
(2021)
Identification of metallic objects using spectral magnetic polarizability tensor signatures: Object characterisation and invariants
in International Journal for Numerical Methods in Engineering
Ledger P
(2022)
Properties of generalized magnetic polarizability tensors
in Mathematical Methods in the Applied Sciences
Title | MPT-Calculator 2022 |
Description | MPT-Calculator is a series of python scripts which calls the NGSolve high order finite element method (FEM) library https://ngsolve.org for computing the magnetic polarizability tensor (MPT) for object characterisation in metal detection. In the case of frequency sweeps, this is accelerated by the Proper Orthogonal Decomposition (POD) technique. It is designed as an educational and research tool for engineers, mathematicians and physicists working both academia and industry and it is hoped those interested in characterising conducting permeable objects will find it useful. The MPT characterises the shape, conductivity, permeability of conducting permeable object, is frequency dependent and is independent of the object's position. The rank 2 MPT is symmetric and has at most 6 independent complex coefficients. However, for objects with mirror or rotational symmetries the number of independent coefficients is smaller. MPT-Calculator computes the MPT using a range of different numerical schemes 1) A hp FEM discretisation of the transmission problems using NGSolve to compute MPT for a single frequency. 2) A hp FEM discretisation of the transmission problems using NGSolve for performing the computation of the MPT over a range of frequencies. 3) A Proper Orthogonal Decomposition (POD) reduced order model, which greatly accelerates the computation of the full order model in 2. for computing the MPT over a range of frequencies. Plots of the computed tensor coefficients as a function of frequency are created and the output data and plots are automatically stored so that they can be recreated, if desired. Recent advances include acceleration of the MPT coefficients and including of prismatic layers for computing highly conducting magnetic objects with thin skin depths. A new set of Jupyter notebook scripts have been created that provide a tutorial and introduction to the software. The technical details of these improvements have been described in a paper which has been submitted for publication. |
Type Of Technology | Software |
Year Produced | 2022 |
Open Source License? | Yes |
Impact | A series of tutorials on use of the software have been given to academic and industrial users in 2022. |
Description | Talk at Keele University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Postgraduate students |
Results and Impact | Around 30 attendees listed to the talk at Keele University, which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2022 |
Description | Talk at Leeds University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Around 30 attendees listed to the talk at Leeds University, which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2022 |
Description | Talk at Swansea University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | Around 30 attendees listed to the talk at Swansea University, which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2022 |
Description | Talk at The Issac Newton Institute, Cambridge |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Around 30 attendees listed to the talk at the Isaac Newton Institute which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2023 |
Description | Talk at The University of Leicester |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | Around 30 attendees listed to the talk at The University of Leicester, which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2022 |
Description | Talk at The University of Nottingham |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Postgraduate students |
Results and Impact | Around 30 attendees listed to the talk at The University of Nottingham, which sparked questions and discussion afterwards, and led to several requests for further information on the material presented. |
Year(s) Of Engagement Activity | 2022 |