sectorsearch

Sectorsearch is a data retrieval technique that partitions a search space into angular sectors, or wedges, typically emanating from a central reference point. Queries are restricted to individual sectors, enabling targeted searches, reduced candidate sets, and opportunities for parallel processing. Sector boundaries are defined by angular ranges and, in some implementations, by radial extents as well.

Applications include geographic information systems, astronomy, robotics, and network analysis. In GIS, sectorsearch supports efficient nearest-neighbor and radial queries around a location by limiting comparisons to the directional sector of interest. In astronomy, it facilitates object finding within predefined angular sectors around a telescope vector. In robotics, sector searches can speed up sensor data fusion and obstacle detection by limiting processing to sectors of the robot’s field of view.

Implementation commonly involves transforming data points to a polar or cylindrical coordinate frame centered on the query location or axis, assigning each point to a sector, and performing a standard range or nearest-neighbor query within the sector. Data structures such as sectorized indexes, angular range trees, or modified spatial indexes are used to support efficient sector pruning and parallel execution across sectors. Overlapping sectors or adaptive sector widths are options to improve boundary handling.

Performance benefits include smaller candidate sets, improved cache locality, and easier parallelization. Limitations include handling objects near sector boundaries, poor performance with highly nonuniform data, and the need to manage sector updates in dynamic datasets. The choice of the number and width of sectors impacts efficiency and must be tuned to the data distribution and query workload.

History and scope: sectorbased partitioning traces roots to radial and angular range queries in spatial databases and has since been applied in GIS and astronomy to improve targeted searches. Related concepts include angular range queries, radial indexing, and sectorized spatial indexes.