US 11,940,557 B2
Object detection device, object detection system, and object detection method
Weijie Liu, Tokyo (JP); Makoto Yasugi, Tokyo (JP); and Yoichi Nakagawa, Tokyo (JP)
Assigned to PANASONIC HOLDINGS CORPORATION, Osaka (JP)
Appl. No. 17/044,652
Filed by Panasonic Corporation, Osaka (JP)
PCT Filed Mar. 28, 2019, PCT No. PCT/JP2019/013640
§ 371(c)(1), (2) Date Oct. 1, 2020,
PCT Pub. No. WO2019/198532, PCT Pub. Date Oct. 17, 2019.
Claims priority of application No. 2018-076081 (JP), filed on Apr. 11, 2018.
Prior Publication US 2021/0103029 A1, Apr. 8, 2021
Int. Cl. G01S 7/41 (2006.01); G01S 13/00 (2006.01); G01S 13/91 (2006.01)
CPC G01S 7/41 (2013.01) [G01S 13/003 (2013.01); G01S 13/91 (2013.01)] 12 Claims
OG exemplary drawing
 
1. An object detection device, comprising:
a communication device configured to perform a first operation for acquirin measurement records of one or more radars,
a processor configured to perform a second operation for detecting an object based on the measurement records of the one or more radars,
wherein the processor is configured to:
acquire settings data for one or more radar grids for measurement, the settings data including location data of cells in the one or more radar grids, each radar grid being set for a measurement area of a corresponding one of the one or more radars and consisting of a plurality of radar cells;
performing clustering operations to define a processing grid, the processing grid being set based on the measurement area of each radar grid and consisting of a plurality of processing cells;
calculate, for each processing cell, one or more likelihood values associated with measurements of one or more radar cells overlapped with the processing cell based on distances between the processing cell and the one or more radar cells, wherein each likelihood value is determined such that a maximum value is a center point of each of the one or more radar cells and the likelihood value decreases with a distance from the center point of each of the one or more radar cells;
calculate a grid value of each of the processing cells based on the one or more likelihood values; and
perform a clustering operation on each processing cell based on at least one of (i) distances between the processing cell and one or more different processing cells, or (ii) the grid value of the processing cell and grid values of the one or more different processing cells.