The Sensor Array Research Programme aims to provide relevant and advanced sensor array processing technologies to the Singapore defense community. The scope of research extends from the physics of signal processes and sensors, through mathematical formulations and algorithm developments, to implementation and experimental investigations. To accelerate the technology developments, the team collaborates extensively and across traditional boundaries between disciplines.
The current research focuses are:
- Robust radio frequency (RF) Array Processing
Robust RF Geolocation and Tracking Methods
- Algorithms that are robust to uncertainties about the sensors and the signal processes.
Advanced Front-End Signal Processing
- Advanced RF emitter localization and tracking methods in urban environments.
- SubNyquist sampling methods and processing.
Automated RF Signal Characterization
- Advanced methods to improve the limitations in analogue front-end and sensors.
Machine Learning for Signal Processing
- To develop signal processing methods to characterize, analyse, compactly represent and classify communication signals.
- To develop novel machine learning algorithms for RF communications and array signal processing.
The team has achieved the following:
- Waveform Aware Robust Adaptive Beamforming for Improved Communications Signal Reception impaired by multipath and impulsive noise.
Developed a Global Positioning System (GPS) free network synchronization for time difference of arrival and frequency difference of arrival (TDOA-FDOA) Geolocation.
- Achieving near optimal signal-to-interference-plus-noise ratio (SINR).
- Ten variants of algorithms transited to DSO.
Ultra-wideband Signal Reception and DF using Sub-Nyquist Processing.
- Optimal algorithm for clock parameters and sensor self-location determination using SOOP.
- Successfully tested on sensors 150km apart with one sensor on a ship using Iridium satellites as donor SOOP. (Transition Ready)
Single Antenna DF. Multiple RF sources DF/ Localization with a single directional antenna.
- Successfully implemented first prototype with DSO (off-line processing).
- Demonstrated expanded capabilities (SPARCO) with photonics sampler and real-time processing (Joint work with Photonics and System-on-chip groups). (Transition Ready)
- Successfully demonstrated sub-Nyquist based DF of ultra-wide reception bandwidth. (Transition Ready)
Joint time difference of arrival and angle of arrival (TDOA-AOA) Geolocation Development for ST-SATCOM.
- Demonstrated successfully using Quad-Copter as Sensor platform in collaboration with School of Computer Science and Engineering (SCE/NTU) and also with FKIE-Fraunhofer’s unmanned aerial vehicle (UAV) platform in Germany. (Transition Ready)
Automatic Modulation Classification and Signal Separation.
- Demonstrated joint TDOA-AOA localization of ground GPS jammers.
- Developed a beacon scheme to enable sensor synchronization to within 10ns.
- Developed methods of automatic modulation classification of up to 64QAM based on higher order statistics with blind signal parameter estimation and tested with real data.
- Developed methods of blind single channel separation of co-channel digital modulation signals for various modulation types ranging from Binary Phase Shift Keying (BPSK) to 64QAM and 64APSK and tested with real data.
- Developed methods of automatic channel codes identification and parameter estimation for a set of channel codes and interleaving types.
Dr Sirajudeen s/o Gulam Razul
Research Director (Sensor Array)
Principal Research Scientist
Phone: +65 67906598