# US 11,994,580 B2 · Electronic device and method for positioning, imaging, detecting, posture discrimination, and shape discrimination > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,994,580 B2 - Document ID: US11994580B2 - Status: Granted - Kind: B2 - Application number: 17/375,418 - Filed: 2021-07-14 - Published: 2022-09-15 - Granted: 2024-05-28 - Earliest claimed: 2021-03-10 - Assignees: Quanta Computer Inc. - Applicants: Quanta Computer Inc. - Inventors: Tsung-Ying Hsieh; Chi-Hsuan Lee - Web page: https://patentgrep.com/patent/US11994580B2 ## CPC - G01S 13/90: using synthetic aperture techniques {, e.g. synthetic aperture radar [SAR] techniques} - G01S 13/04: Systems determining presence of a target (based on relative movement of target G01S13/56) - G01S 13/42: Simultaneous measurement of distance and other co-ordinates (indirect measurement G01S13/46) - G01S 13/87: Combinations of radar systems, e.g. primary radar and secondary radar - G01S 13/89: for mapping or imaging - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES ## Abstract An electronic device includes a plurality of radars and at least one processor. Each of the radars includes at least one transmitting antenna and a plurality of receiving antennas arranged as a two-dimensional array antenna. The processor converts the RF signal received by the receiving antennas into a ranging profile that records the distance between each of the receiving antennas and the target and the receiving intensity corresponding to the distance. The processor generates a voxel profile to indicate the relationship between the distance and the receiving intensity in three-dimensional space. The processor performs a point generation algorithm to generate a plurality of points in three-dimensional space according to the voxel profile and the receiving intensity threshold. The processor performs a cluster analysis algorithm to identify a plurality of target points corresponding to the target among the points to obtain the position of the target. ## Claims ### Claim 1 An electronic device for positioning, imaging, detecting, posture discrimination and shape discrimination of a target, comprising: a plurality of radars, wherein each of the radars comprises at least one transmitting antenna and a plurality of receiving antennas, and the receiving antennas are arranged as a two-dimensional array antenna; at least one processor, operative to: convert the RF signal received by the receiving antennas into a ranging profile; wherein the ranging profile records a distance between each of the receiving antennas and the target and a receiving intensity corresponding to the distance; generate a voxel profile to indicate the relationship between the distance and the receiving intensity in three-dimensional space; perform a point generation algorithm to generate a plurality of points in three-dimensional space according to the voxel profile and a receiving intensity threshold, wherein the point generation algorithm comprises regarding a coordinate point and the area surrounding the coordinate point as having no point in three-dimensional space in the voxel profile when the difference between the receiving intensity of the coordinate point corresponding to the distance and the receiving intensity around the coordinate point is less than or equal to the receiving intensity threshold, and regarding the coordinate point and the area surrounding the coordinate point as the same point in three-dimensional space in the voxel profile when the difference between the receiving intensity of the coordinate point corresponding to the distance and the receiving intensity around the coordinate point is greater than the receiving intensity threshold; and perform a cluster analysis algorithm to identify a plurality of target points corresponding to the target among the points to obtain the position of the target. ### Claim 2 (depends on 1) The electronic device as claimed in claim 1, wherein the radars are frequency modulated continuous wave (FMCW) radars, pulse radars, pulse Doppler radars, pulse coherent radars, orthogonal frequency-division multiplexing (OFDM) radars, or stepped frequency continuous wave (SFCW) radars. ### Claim 3 (depends on 2) The electronic device as claimed in claim 2, wherein when the radars are FMCW radars, the processor converts the RF signal received by the receiving antennas into the ranging profile using a Fast Fourier Transform (FFT). ### Claim 4 (depends on 2) The electronic device as claimed in claim 2, wherein when the radars are FMCW radars, the transmitting antenna of each of the radars transmits RF signals whose frequency changes over time, and the processor calculates the distance between the receiving antennas and the target according to the frequency of the RF signal received by the receiving antennas. ### Claim 5 (depends on 1) The electronic device as claimed in claim 1, wherein the processor is further operative to control the transmission period of the at least one transmitting antenna of each of the radars, so that the at least one transmitting antenna sequentially transmits the RF signal at a predetermined time interval. ### Claim 6 (depends on 1) The electronic device as claimed in claim 1, wherein the processor performs the cluster analysis algorithm, comprising: regarding one of the points and its neighboring points as being in the same cluster in three-dimensional space when the distance between the one of the points and its neighboring points is within a preset distance; and regarding all points in the cluster in three-dimensional space as target points corresponding to the target when the number of all points included in the cluster is greater than a preset number. ### Claim 7 (depends on 1) The electronic device as claimed in claim 1, wherein the point generation algorithm comprises an ordered statistic CFAR (OS-CFAR); and the cluster analysis algorithm comprises a Density-Based Spatial Clustering of Applications with Noise algorithm. ### Claim 8 A method for positioning, imaging, detecting, posture discrimination and shape discrimination of a target, applicable to an electronic device comprising a plurality of radars and at least one processor, wherein each of the radars comprises at least one transmitting antenna and a plurality of receiving antennas arranged in an array antenna, the method comprising: converting the RF signal received by the receiving antennas into a ranging profile; wherein the ranging profile records the distance between each of the receiving antennas and the target, and the receiving intensity corresponding to the distance; generating a voxel profile to indicate the relationship between the distance and the receiving intensity in three-dimensional space; performing a point generation algorithm to generate a plurality of points in three-dimensional space according to the voxel profile and the receiving intensity threshold, wherein the point generation algorithm comprises regarding a coordinate point and the area surrounding the coordinate point as having no point in three-dimensional space in the voxel profile when the difference between the receiving intensity of the coordinate point corresponding to the distance and the receiving intensity around the coordinate point is less than or equal to the receiving intensity threshold, and regarding the coordinate point and the area surrounding the coordinate point as the same point in three-dimensional space in the voxel profile when the difference between the receiving intensity of the coordinate point corresponding to the distance and the receiving intensity around the coordinate point is greater than the receiving intensity threshold; and performing a cluster analysis algorithm to identify a plurality of target points corresponding to the target among the points to obtain the position of the target. ### Claim 9 (depends on 8) The method as claimed in claim 8, wherein performing the cluster analysis algorithm comprises: regarding one of the points and its neighboring points as being in the same cluster in three-dimensional space when the distance between the one of the points and its neighboring points is within a preset distance; and regarding all points in the cluster in three-dimensional space as target points corresponding to the target when the number of all points included in the cluster is greater than a preset number.