Sensor Signal Processing
Lead Research Organisation:
Heriot-Watt University
Department Name: Sch of Engineering and Physical Science
Abstract
The fundamental challenges for signal processing are: how best to sense; how to distribute the processing and communication of the data within the network to maximize performance and minimize cost; how to analyze it to extract the salient information. Signal processing is the glue which holds together much of modern technology. The algorithms underpinning mobile communications, medical imaging, image rendering for games and many other technologies were all developed within the global signal and image processing research community. Today the world is an environment of pervasive interconnected sensing with the associated requirement to extract useful information from the large volumes of data that arise. In applications of defence, homeland security and environmental monitoring there is a need to collect and combine data from a range of sensors of widely differing complexity (e.g. from satellite imaging to ground based motion detectors) to achieve persistent wide area monitoring of a scene of interest. This can assist in the assessment of threats, e.g. the planting of improvised explosive devices, the long-term ecological effects of deforestation, or the monitoring of time critical events such as devastation by fire or flood. On the roads the external monitoring of traffic flow by closed circuit television networks, junction-based pressures sensors and GPS create an opportunity when combined with on-vehicle sensors (e.g. lidar, radar and video) to provide driver assistance and ultimately automatic driving systems. This Platform proposal seeks funding for a foundation for our research team in addressing these challenges.
Planned Impact
Actions we propose within our Platform to deliver impact are as follows:
(i) Enable a range of research projects to be undertaken, specifically:
a. Exploratory projects will allow risky but potentially ground-breaking ideas to be explored.
b. Reactive projects which permit a rapid response to exciting and unexpected new approaches that arise from our own research or from international groups;
Both of the above approaches provide a pathway to delivering impact to our academic community.
c. Proof of concept studies with our industrial partners to explore early implementation of our algorithms;
The above allows us to accelerate the uptake of our research by industry by working directly with them to implement our algorithms in systems, if successful this would offer significant opportunities for economic impact.
(ii) Provide continuity and bridging funds to retain key postdoctoral researchers and exceptional graduating PhD students thus allowing longer term career planning;
(iii) Facilitate strong interaction with other research communities for application-specific sensing challenges via interdisciplinary workshops with industrial and academic collaborators, (outputs could highlight research trends, develop position papers and initiate short-term feasibility studies;
(iv) Develop and enhance our collaborations via two-way exchanges with industrial and international research teams via extended stays (1-month) in major international laboratories for our researchers.
All of the above ensure that our PDRAs have superb opportunities to develop their careers by offering them stability in their career at a critical time, presenting opportunities to interact with colleagues in the international research community, and also to engage with industry to see their algorithmic research implemented in potential products.
(i) Enable a range of research projects to be undertaken, specifically:
a. Exploratory projects will allow risky but potentially ground-breaking ideas to be explored.
b. Reactive projects which permit a rapid response to exciting and unexpected new approaches that arise from our own research or from international groups;
Both of the above approaches provide a pathway to delivering impact to our academic community.
c. Proof of concept studies with our industrial partners to explore early implementation of our algorithms;
The above allows us to accelerate the uptake of our research by industry by working directly with them to implement our algorithms in systems, if successful this would offer significant opportunities for economic impact.
(ii) Provide continuity and bridging funds to retain key postdoctoral researchers and exceptional graduating PhD students thus allowing longer term career planning;
(iii) Facilitate strong interaction with other research communities for application-specific sensing challenges via interdisciplinary workshops with industrial and academic collaborators, (outputs could highlight research trends, develop position papers and initiate short-term feasibility studies;
(iv) Develop and enhance our collaborations via two-way exchanges with industrial and international research teams via extended stays (1-month) in major international laboratories for our researchers.
All of the above ensure that our PDRAs have superb opportunities to develop their careers by offering them stability in their career at a critical time, presenting opportunities to interact with colleagues in the international research community, and also to engage with industry to see their algorithmic research implemented in potential products.
Organisations
Publications
Buller G
(2018)
Restoration Of Multilayered Single-Photon 3D Lidar Images
Altmann Y
(2016)
Robust Bayesian target detection algorithm for depth imaging from sparse single-photon data
in IEEE Transactions on Computational Imaging
D'Arca E
(2016)
Robust indoor speaker recognition in a network of audio and video sensors
in Signal Processing
Altmann Y
(2015)
Robust Linear Spectral Unmixing using Anomaly Detection
Altmann Y
(2015)
Robust Linear Spectral Unmixing Using Anomaly Detection
in IEEE Transactions on Computational Imaging
Altmann Y
(2015)
Robust linear spectral unmixing using outlier detection
Halimi A
(2020)
Robust Restoration of Sparse Multidimensional Single-Photon LiDAR Images
in IEEE Transactions on Computational Imaging
Altmann Y
(2017)
Robust Spectral Unmixing of Sparse Multispectral Lidar Waveforms Using Gamma Markov Random Fields
in IEEE Transactions on Computational Imaging
Halimi A
(2016)
Robust Unmixing Algorithms for Hyperspectral Imagery
Andrecki M
(2015)
Sensor Management with Regional Statistics for the PHD Filter
Fisher KM
(2016)
SERS as a tool for in vitro toxicology.
in Faraday discussions
Kelly S
(2014)
Sparsity-based autofocus for undersampled synthetic aperture radar
in IEEE Transactions on Aerospace and Electronic Systems
Pailhas Y
(2017)
Spatially Distributed MIMO Sonar Systems: Principles and Capabilities
in IEEE Journal of Oceanic Engineering
Bryant D
(2015)
Spawning Models for the CPHD Filter
Altmann Y
(2018)
Spectral classification of sparse photon depth images.
in Optics express
Altmann Y
(2015)
Spectral Unmixing of Multispectral Lidar Signals
in IEEE Transactions on Signal Processing
Yaghoobi M
(2013)
Super-resolution Sparse Projected Capacitive Multitouch Sensing
Altmann Y
(2016)
Target detection for depth imaging using sparse single-photon data
Bryant D
(2017)
The CPHD Filter With Target Spawning
in IEEE Transactions on Signal Processing
Mulgrew B
(2014)
The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing
in IEEE Transactions on Signal Processing
Auger F
(2013)
Time-Frequency Reassignment and Synchrosqueezing: An Overview
in IEEE Signal Processing Magazine
Pailhas Y
(2017)
Tracking with MIMO sonar systems: applications to harbour surveillance
in IET Radar, Sonar & Navigation
Blair C
(2016)
Video Anomaly Detection in Real Time on a Power-Aware Heterogeneous Platform
in IEEE Transactions on Circuits and Systems for Video Technology
Bonnel J
(2017)
Waveguide mode amplitude estimation using warping and phase compensation.
in The Journal of the Acoustical Society of America
Ren X
(2018)
Wavelength-time coding for multispectral 3D imaging using single-photon LiDAR.
in Optics express
Pailhas Y
(2015)
Wideband CDMA Waveforms for Large MIMO Sonar Systems
Description | This grant was focused on developing advanced signal processing methods for a wide range of application domains. |
Exploitation Route | Our work will be taken forward in several ways 1. In the development of advanced SAR systems by industry, e.g. Selex ES. 2. By Medical companies such as GE in developing new MRI scanning methods. 3. By Life Science companies in analysing their data e.g Agilent |
Sectors | Electronics,Healthcare,Security and Diplomacy |
Description | Publications form this grant have led to the development of two pieces of software used by companies to improve their systems. |
First Year Of Impact | 2015 |
Sector | Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software) |
Impact Types | Economic |
Description | AFRL-AFOSR |
Amount | $75,000 (USD) |
Funding ID | AFRL-AFOSR-UK-TR-2014-0027 |
Organisation | Air Force Research Laboratory |
Sector | Public |
Country | United States |
Start | 02/2014 |
End | 06/2014 |
Description | Agilent Research Collaboration (IAA funds) 2013-14 |
Amount | £20,000 (GBP) |
Organisation | Agilent Technologies |
Sector | Private |
Country | United States |
Start | 04/2013 |
End | 10/2013 |
Description | Agilent Research Collaboration (IAA funds) 2014-15 |
Amount | £27,000 (GBP) |
Organisation | Agilent Technologies |
Sector | Private |
Country | United States |
Start | 06/2014 |
End | 06/2015 |
Description | BAe |
Amount | £22,000 (GBP) |
Organisation | BAE Systems |
Department | BAE Systems Electronics Systems |
Sector | Private |
Country | United Kingdom |
Start | 01/2015 |
End | 12/2015 |
Description | DGA Fellowship |
Amount | € 53,000 (EUR) |
Organisation | Directors Guild of America (DGA) Foundation |
Sector | Charity/Non Profit |
Country | United States |
Start | 01/2014 |
End | 12/2014 |
Description | FP7-ITN |
Amount | € 840,000 (EUR) |
Funding ID | 607774 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 01/2014 |
End | 12/2017 |
Description | FP7-ITN |
Amount | € 320,000 (EUR) |
Funding ID | MacSeNet 642685 (H2020) |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 09/2014 |
End | 09/2018 |
Description | FP7-ITN |
Amount | € 546,575 (EUR) |
Funding ID | SpaRTAN 607290 (FP7) |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 03/2015 |
End | 04/2018 |
Description | GE Global Research 2014-15 |
Amount | $328,000 (USD) |
Organisation | General Electric |
Sector | Private |
Country | United States |
Start | 11/2014 |
End | 04/2016 |
Description | Keysight Donations |
Amount | £6,000 (GBP) |
Funding ID | 4169 |
Organisation | Keysight Technologies |
Sector | Private |
Country | United States |
Start | 10/2015 |
End | 03/2016 |
Description | Responsive Mode |
Amount | £601,000 (GBP) |
Funding ID | EP/M008916/1 (Edinburgh), EP/M008843/1 (HWU) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2015 |
End | 02/2018 |
Description | SEA Ltd |
Amount | £16,500 (GBP) |
Organisation | Systems Engineering & Assessment Ltd |
Sector | Private |
Country | United Kingdom |
Start | 01/2014 |
End | 12/2014 |
Description | Selex ES Inter Mural Funding |
Amount | £18,600 (GBP) |
Organisation | Selex ES |
Department | SELEX Galileo Ltd |
Sector | Private |
Country | United Kingdom |
Start | 01/2016 |
End | 12/2016 |
Description | US Dept Homeland Security |
Amount | $328,000 (USD) |
Organisation | Government of the United States of America |
Department | Department of Homeland Security |
Sector | Public |
Country | United States |
Start | 05/2014 |
End | 06/2016 |
Title | Fast parallel SAR back projection code |
Description | Developed novel method for fast back projection code for Synthetic Aperture Radar System |
Type Of Technology | New/Improved Technique/Technology |
Year Produced | 2015 |
Impact | Software was Licensed to Selex ES, work was done jointly under two grants EP/K0142771/1 and EP/J015180/1 |
Title | Parametric Dictionary Design and Constrained Overcomplete Analysis Operator Learning for Cosparse Signal Modelling |
Description | Software which enables more efficient STAP radar systems and was used in the i-STAR demonstration radar system by DSTL |
Type Of Technology | New/Improved Technique/Technology |
Year Produced | 2015 |
Impact | Software used by UK industry to explore application of software to Radar systems |
URL | http://www.mehrdadya.com |