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UID:4647-1610445600-1610449200@ece.northeastern.edu
SUMMARY:ECE PhD Proposal Review: Haoqing Li
DESCRIPTION:PhD Proposal Review: Robust Processing against Interferences in GNSS Navigation \nHaoqing Li \nLocation: Zoom Link \nAbstract: Satellite-based navigation is prevalent as positioning applications among our lives\, how-ever\, this high reliance brings potential threats when different interferences and jamming signals are considered. Jamming devices\, although illegal in many countries\, can be easily to get. Those devices can broadcast high-power jamming signals in Global Navigation Satellite System (GNSS) frequency band to destroy receiver’s performance. While jamming signals are illegal and we may get rid of it with the power of law\, other kinds of interferences will cannot even be avoided. Distance Measuring Equipment (DME) signal is applied to measure the distance between aircraft and ground station\, significant in aircraft transport but interference in GNSS processing. Besides\, the GNSS signal itself can also be a interference after reflection and refraction. Since we couldn’t simply re-move those from the source\, methods to mitigate influences of interferences is necessary for stable performance of receiver. There are three main blocks in GNSS receiver: acquisition block\, tracking block and positioning block\, where influence of interferences could be eliminate to get an accurate Position\, Velocity\, and Time (PVT) solution. In this article\, robust statistics processing is applied as one of the interference mitigation methods. This method aims to lower influence of outliers\, which is the presence of many kinds of interferences in either time domain or transformed domain. Robust statistics processing can be used in pre-correlation in both acquisition block and tracking block\, while a robust Kalman filter is designed in positioning block to get rid of interferences. Deep learning\, achieving extraordinary performance in many application domains\, also provides improvement to tracking block against multipath problem. A deep neural network is built to substitute the whole tracking loop to bring robustness to receiver.
URL:https://ece.northeastern.edu/event/ece-phd-proposal-review-haoqing-li/
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