Improved gnss-r altimetry methods: Theory and experimental demonstration using airborne dual frequency data from the microwave interferometric reflectometer (mir)

Altimetric performance of Global Navigation Satellite System - Reflectometry (GNSS-R) instruments depends on receiver’s bandwidth and signal-to-noise ratio (SNR). The altimetric delay is usually computed from the time difference between the peak of the direct signal waveform and the maximum of the derivative of the reflected signal waveform. Dual-frequency data gathered by the airborne Microwave Interferometric Reflectometer (MIR) in the Bass Strait, between Australia and Tasmania, suggest that this approach is only valid for flat surfaces and large bandwidth receivers. This work analyses different methods to compute the altimetric observables using GNSS-R. A proposed novel methodThis work was funded by the Spanish Ministry of Science, Innovation and Universities, “Sensing with Pioneering Opportunistic Techniques”, grant RTI2018-099008-B-C21/AEI/10.13039/ 501100011033, and the grant for recruitment of early-stage research staff FI-DGR 2015 of the AGAUR— Generalitat de Catalunya (FEDER), Spain, and the grant for recruitment of early-stage research staff FI 2018 of the AGAUR—Generalitat de Catalunya (FEDER), Spain, and Unidad de Excelencia María de Maeztu MDM-2016-060Postprint (published version

Improved GNSS-R Altimetry Methods: Theory and Experimental Demonstration Using Airborne Dual Frequency Data from the Microwave Interferometric Reflectometer (MIR)

Altimetric performance of Global Navigation Satellite System - Reflectometry (GNSS-R) instruments depends on receiver’s bandwidth and signal-to-noise ratio (SNR). The altimetric delay is usually computed from the time difference between the peak of the direct signal waveform and the maximum of the derivative of the reflected signal waveform. Dual-frequency data gathered by the airborne Microwave Interferometric Reflectometer (MIR) in the Bass Strait, between Australia and Tasmania, suggest that this approach is only valid for flat surfaces and large bandwidth receivers. This work analyses different methods to compute the altimetric observables using GNSS-R. A proposed novel method, the Peak-to-Minimum of the 3rd Derivative (P-Min3D) for narrow-band codes (e.g., L1 C/A), and the Peak-to-Half Power (P-HP) for large bandwidth codes (e.g., L5 or E5a codes) show improved performance when using real data. Both methods are also compared to the Peak-to-Peak (P-P) and Peak-to-Maximum of the 1st Derivative (P-Max1D) methods. The key difference between these methods is the determination of the delay position in the reflected signal waveform in order to compute the altimetric observable. Airborne experimental results comparing the different methods, bands and GNSS-R processing techniques show that centimeter level accuracy can be achieved

Improved GNSS-R altimetry methods: experimental demonstration using dual frequency data

Altimetric performance of Global Navigation Satellite System - Reflectometry (GNSS-R) instruments is highly dependent on receiver's bandwidth. The altimetric delay is usually computed from the time difference between the peak of the direct signal waveform, and the maximum of the derivative of the reflected signal waveform. Dual frequency data gathered by the MIR (Microwave Interferometric Reflectometer) in the Bass Strait suggests that this approach is only valid for flat surfaces, and large bandwidth receivers. This work presents and analyses improved methods to compute the altimetric observables using GNSS-R. They show improved performance when using real data. These novel methods are the Peak-to-Minimum of the 3rd Derivative for narrow-band codes (e.g. L1 C/A), and the Peak-to-Half Power (mid-rise leading-edge) for large bandwidth codes (e.g. L5 or E5a codes). The key difference between these methods is the determination of the delay position in the reflected signal waveform in order to compute the altimetric observable. Airborne experimental results comparing the different methods, bands and GNSS-R processing techniques show that centimeter level accuracy can be achieved

Advanced GNSS-R signals processing with GPU

Treball de fi de grau en Sistemes AudiovisualsTutors: Albert Guillen, Adriano Camps, Daniel PascualGlobal Navigation Satellite Systems (GNSS) are mainly used for positioning. Nonetheless part of those signals emitted towards the Earth are reflected and can be used for GNSS-Reflectometry (GNSS-R), a novel Earth Observation technique. The Remote Sensing Lab has developed the Microwave Interferometric Radiometer (MIR) in order to capture direct and reflected signals from GNSS constellations. In order to extract information form the signals, these ones need to be processed. In many cases, the first approach of processing them sequentially with common tools, such as Matlab, is not feasible due to the time cost. More specific alternatives have to be found in order to process the large amounts of data. This study requires the analysis of GNSS-R techniques as well as the analysis of the different options of implementation. This Degree Thesis is the development of a time-efficient Data Processing Unit (DPU) to process the raw signals from the MIR instrument.El principal us dels sistemes de posicionament per satèl·lit (Global Navigation Satellite Systems, GNSS) es la navegació i localització. Part de les ones que emeten aquests satèl·lits reboten a la superfocie de la Terra. Si es capten aquestes senyals es poden utilitzar per observar la Terra, aquesta tecnica en concret s’anomena GNSS-Reflectometry. El Remote Sensing Lab ha creat el Microwave Interferometric Radiometer (MIR) per captar la senyal directa i reflectida de senyals de satèl·lit GNSS. Per poder-ne extraure la informacio de la terra, aquestes senyals primer s’han de processar. Es un proces complex i les opcions més típiques per processar dades com Matlab son ineficients ja que requereix massa temps. Per trobar un bon candidat per processar grans quantitats de dades es necessari realitzar un estudi de les tecniques utilitzades en GNSS-R i estudiar diferents opcions d’implementació. En aquest treball de fi de grau s’exposa el desenvolupament d'un Data Processing Unit (DPU) per processar les dades del MIR