Signal Processing 4 the Networked Battlespace

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Engineering

Abstract

Sensors have for a long time played a vital role in battle awareness for all our armed forces, ranging from advanced imaging technologies, such as radar and sonar to acoustic and the electronic surveillance. Sensors are the "eyes and ears" of the military providing tactical information and assisting in the identification and assessment of threats. Integral in achieving these goals is signal processing. Indeed, through modern signal processing we have seen the basic radar transformed into a highly sophisticated sensing system with waveform agility and adaptive beam patterns, capable of high resolution imaging, and the detection and discrimination of multiple moving targets.
Today, the modern defence world aspires to a network of interconnected sensors providing persistent and wide area surveillance of scenes of interest. This requires the collection, dissemination and fusion of data from a range of sensors of widely varying complexity and scale - from satellite imaging to mobile phones. In order to achieve such interconnected sensing, and to avoid the dangers of data overload, it is necessary to re-examine the full signal processing chain from sensor to final decision.
The need to reconcile the use of more computationally demanding algorithms and the potential massive increase in data with fundamental resource limitations, both in terms of computation and bandwidth, provides new mathematical and computational challenges. This has led in recent years to the exploration of a number of new techniques, such as, compressed sensing, adaptive sensor management and distributed processing techniques to minimize the amount of data that is acquired or transmitted through the sensor network while maximizing its relevance. While there have been a number of targeted research programs to explore these new ideas, such as the USs "Integrated Sensing and Processing" program and their "Analog to Information" program, this field is still generally in its infancy.
This project will study the processing of multi-sensor systems in a coherent programme of work, from efficient sampling, through distributed data processing and fusion, to efficient implementations. Underpinning all this work, we will investigate the significant issues with implementing complex algorithms on small, lighter and lower power computing platforms. Exemplar challenges will be used throughout the project covering all major sensing domains - Radar/radio frequency, Sonar/acoustics, and electro-optics/infrared - to demonstrate the performance of the innovations we develop.

Planned Impact

The impact of the proposed research will be manifold. The military have an aspiration of a network of interconnected sensors providing persistent and wide area surveillance of scenes of interest, and to this end have invested heavily in a Network Enabled Capability (NEC) of satellites and ground stations linking to unmanned vehicles, platforms and drones. Such a capability will provide an important operational advantage to our armed forces. The research in this project, examining the acquisition and processing of information from multi-sensor systems in an integrated manner, will help them realize this capability.
Furthermore, as the research project aims to work closely with the UK defence industries there is likely to be a significant economic benefit. A successful project will translate into greater technology pull through of our research ideas into the commercial sector and will help our defence companies remain at the leading edge in the international defence market.
Beyond the defence sector this work will impact on many other disciplines that will benefit from the development of improved sensing systems, with reduced computation and power costs, including: robotics, astronomy, remote sensing and medicine.
Finally our proposed research sits right at the heart of the EPSRC intelligent information infrastructure (TI3) vision to "intelligently manage massive amounts of data, ensure efficient communications and exploit the content and information that will be available." It will therefore impact on a range of related academic areas from mathematics and statistics, through computer science to the engineering of novel sensing systems in areas such as surveillance and medicine.
 
Description This project is now in its third year.

Research into low complexity sub Nyquist samplnig using efficient fractional delays through delay compensated TF transforms has offered some novel ideas.

Our distributed multi-sensor processing work has moved on considerably to provide improved scalability and has overcome issues of resource limitations such as communication bandwidth and power.

Current research focus in underwater sonar systems and in particular Multiple Input Multiple Output (MIMO) systems has developed new algorithms which enhance the capabilities and performances of current MIMO systems.

Our work on audio-video tracking has focused on the development of new probabilistic behaviourial recognition models that have led to a number of publications.

Novel algorithms for multiple target tracking has been developed in a closed-loop sensor management context.

Work has also focused on efficient implementations of Gaussian Processes to support classification with confidence.

There has already been considerable exploitation and technology transfer from this project - see narrative impact for details.

In October 2015 we successfully passed our mid term review.
Exploitation Route The project is ongoing
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software)

URL http://www.mod-udrc.org
 
Description The research from this project has led to a number of enabling contracts with Dstl, these are listed below: ED TIN 2-1 Tracking and Association- State of the Art Review, £12k + VAT. This is now completed, follow-on work and has led to ED TIN 2-5. This project looked at multi-target tracking algorithms for space surveillance applications and key methods were presented for this scenario. ED TIN 2-2 Application of novel tracking and association methods for Space Situational Awareness (SSA), £25k + VAT. This is now complete. Processed raw data from ground-based radars and optical sensor systems provided by Dstl, and proposed the corresponding realistic sensor models in order to solve the multi-orbit determination problem. This illustrated the novel filtering framework works on real data. ED TIN 2-3 Innovative underwater track motion analysis concepts, Research Associate employed for 1 year, £127k + VAT for 12mths: Project Started 5/1/15 and ended 30/12/15. This project identified an algorithmic solution to multi-sensor and tracking challenges in submarines and this work will be utilised in designing the submarines of the future. ED TIN2-4 Spectral De-convolution, £13k + VAT. Project completed and further work see ED TIN2-6. Designed a raman spectral deconvolution model and tested successfully on Dstl data. ED TIN 2-5 Tracking and Association - State of the Art Review £115057.50, in progress. Follow-on work looking at more specific algorithms, finite set statistics and applying to Dstl data for space surveillance challenges. ED TIN2-6 Deconvolution of Raman Spectral Mixtures 2, £36550 in total, complete. Developed a greedy sparse raman spectral unmixing algorithm with a simple baseline correction step with a low memory usage. Dstl have set up contract with UoE and Snowie Range Instruments to develop demonstrator. ED TIN2-7 Temporal Anomaly Detection challenge,£85787.50, started and due to finish 31/12/16. The aim of this project is to provide signal processing algorithms to discover anomalies in noisy video surveillance data given by Dstl. ED TIN2-8 Mobile Ad-Hoc Sensor Network (MASNET) Modelling Task, £120K, a researcher will be employed for 12 months, started - kick off meeting March 2016. The aim of this work is to the characterise the use of a Mobile Ad Hoc network in two generic scenarios; rural and urban. ED TIN2-9 Chirplet Transform Technique - Further development of a chirplet transform technique for the detection and characterisation of radar signals, £7785 + VAT: Complete. Review and tested code and delivered with the demonstration scripts and provide technical support as required when Dstl integrate with the QinetiQ test bench.
First Year Of Impact 2013
Sector Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Electronics
Impact Types Policy & public services