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Within our Signal Processing business line, we study and develop algorithms and technologies that are used in low-power signal detection, isolation, characterisation, classification, and localisation. These can be applied in various industries and fields of science, for example, in Earth Observation satellites to detect and filter out anthrophogenic signals (interference), in telecommunications to monitor the use of the electromagnetic spectrum, and in electronic warfare for signal intelligence and electronic support measures (ESM). Real-time, efficient, light weight, and resource-friendly digital signal processing algorithms and technologies are required in all applications. Some of our reference projects are presented below. We are currently active in the development of:
Anthropogenic Radio Frequency Interference (RFI) within microwave radiometer bands is a serious problem in remote sensing. In the “Radio Frequency Interference (RFI) Processor” R&D project, Harp Technologies developed a signal processing module to detect and blank the RFI in real time. The processor was designed to be compatible with the 18.7-GHz channel of the Microwave Imager (MWI) instrument on board the European MetOp Second Generation satellite system. The processor has two input channels that work in parallel and it incorporates three different detection algorithms. The processing is implemented in a reprogrammable FPGA. The project was funded by the European Space Agency (ESA) and the project partner was the Technical University of Denmark, National Space Institute (DTU Space).
Harp Technologies is developing an interference analysis and mitigation tool for the European Space Agency (ESA) in the context of the Galileo European global satellite-based navigation system. Unintentional and intentional interferences like jamming and spoofing may harm any satellite-based navigation system. In order to study interference detection, isolation, classification, and localisation techniques in the Galileo context, the simulator under development mimics space-borne receivers and their reception under such interference threats. In the simulator environment, special emphasis has been put on machine learning algorithms in the classification process of interference signals (state vector machines, feature-based classification).
Harp Technologies has developed a real-time signal detection and analysis sensor demonstrator to study on-ground emitter localisation from small satellites. The sensor demonstrator is configurable to receive signals within the 0-6 GHz band with 50 MHz of instantaneous bandwidth. Advanced real-time digital signal processing algorithms have been implemented in FPGA and an ultra-stable GNSS-synchronised reference oscillator has been implemented to combine results from multiple sensors (platforms). This facilitates high-accuracy emitter localisation. The design concept is suitable for signal detection and emitter localisation systems on-board unmanned aerial vehicles (UAVs) and small satellites, for example.
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