{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/144899"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/144899","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Multi-Domain Coincidence Processing and Memory Architecture for Real-Time Geiger Mode LiDAR","abstract":"Geiger-Mode LiDAR is a powerful time-of-flight range sensing technology that enables rapid, wide area three-dimensional mapping with the unique capability of foliage penetration. These sensor arrays produce very high data rates on the order of 5 Gbps, requiring high-bandwidth motion compensation and coincidence processing to correlate the range returns and locate the modes in three-dimensional space. This paper proposes a multi-processor system architecture and memory management techniques for performing orientation-compensated histogram generation and peak detection to filter the LiDAR data stream, removing redundancy and spurious outputs. The multi-processor design, employing custom logic in concert with multiple CPUs, offers a reduction in system size, weight, and power [SWaP] by several orders of magnitude when compared to existing CPU-only real time coincidence processor designs. Behavioral simulations and hardware-in-the-loop testing offer partial proof of functionality for this design, which is capable of reducing the data rate by a factor of approximately 300 with output in the form of Cartesian coordinates, which can be directly integrated into a point cloud data structure for viewing. This promising result warrants further development work on LiDAR system designs incorporating these concepts.","abstract_html":"Geiger-Mode LiDAR is a powerful time-of-flight range sensing technology that enables rapid, wide area three-dimensional mapping with the unique capability of foliage penetration. These sensor arrays produce very high data rates on the order of 5 Gbps, requiring high-bandwidth motion compensation and coincidence processing to correlate the range returns and locate the modes in three-dimensional space. This paper proposes a multi-processor system architecture and memory management techniques for performing orientation-compensated histogram generation and peak detection to filter the LiDAR data stream, removing redundancy and spurious outputs. The multi-processor design, employing custom logic in concert with multiple CPUs, offers a reduction in system size, weight, and power [SWaP] by several orders of magnitude when compared to existing CPU-only real time coincidence processor designs. Behavioral simulations and hardware-in-the-loop testing offer partial proof of functionality for this design, which is capable of reducing the data rate by a factor of approximately 300 with output in the form of Cartesian coordinates, which can be directly integrated into a point cloud data structure for viewing. This promising result warrants further development work on LiDAR system designs incorporating these concepts.","abstract_has_math":false,"creators":["McGuire, Jacob T."],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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These sensor arrays produce very high data rates on the order of 5 Gbps, requiring high-bandwidth motion compensation and coincidence processing to correlate the range returns and locate the modes in three-dimensional space. This paper proposes a multi-processor system architecture and memory management techniques for performing orientation-compensated histogram generation and peak detection to filter the LiDAR data stream, removing redundancy and spurious outputs. The multi-processor design, employing custom logic in concert with multiple CPUs, offers a reduction in system size, weight, and power [SWaP] by several orders of magnitude when compared to existing CPU-only real time coincidence processor designs. Behavioral simulations and hardware-in-the-loop testing offer partial proof of functionality for this design, which is capable of reducing the data rate by a factor of approximately 300 with output in the form of Cartesian coordinates, which can be directly integrated into a point cloud data structure for viewing. This promising result warrants further development work on LiDAR system designs incorporating these concepts."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["Multi-Domain Coincidence Processing and Memory Architecture for Real-Time Geiger Mode LiDAR"]}]}],"canonical_facts":{"dc:contributor.advisor":["Rowe, Gregory","Steinmeyer, Joe","Vasile, Alexandru"],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:creator":["McGuire, Jacob T."],"dc:date.accessioned":["2022-08-29T16:19:35Z"],"dc:date.available":["2022-08-29T16:19:35Z"],"dc:date.issued":["2022-05"],"dc:description.abstract":["Geiger-Mode LiDAR is a powerful time-of-flight range sensing technology that enables rapid, wide area three-dimensional mapping with the unique capability of foliage penetration. These sensor arrays produce very high data rates on the order of 5 Gbps, requiring high-bandwidth motion compensation and coincidence processing to correlate the range returns and locate the modes in three-dimensional space. This paper proposes a multi-processor system architecture and memory management techniques for performing orientation-compensated histogram generation and peak detection to filter the LiDAR data stream, removing redundancy and spurious outputs. The multi-processor design, employing custom logic in concert with multiple CPUs, offers a reduction in system size, weight, and power [SWaP] by several orders of magnitude when compared to existing CPU-only real time coincidence processor designs. Behavioral simulations and hardware-in-the-loop testing offer partial proof of functionality for this design, which is capable of reducing the data rate by a factor of approximately 300 with output in the form of Cartesian coordinates, which can be directly integrated into a point cloud data structure for viewing. This promising result warrants further development work on LiDAR system designs incorporating these concepts."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/144899"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright MIT"],"dc:rights.uri":["http://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Multi-Domain Coincidence Processing and Memory Architecture for Real-Time Geiger Mode LiDAR"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Engineering in Electrical Engineering and Computer Science"]},"updated_at":"2026-07-22T22:20:47Z"}