-
公开(公告)号：US12092759B2
公开(公告)日：2024-09-17
申请号：US17565870
申请日：2021-12-30
发明人： Michael Meyer , Georg Kuschk
IPC分类号： G01S7/41 , G01S7/295 , G01S13/931 , G06N3/0455 , G06N3/088
CPC分类号： G01S7/417 , G01S7/295 , G06N3/0455 , G06N3/088 , G01S13/931
摘要： A radar sensor system receives or generates radar data indicative of radar returns received at an antenna array. An encoder neural network encodes the radar data into first embeddings defined in a first latent space. A transformer neural network receives the first embeddings and transforms the first embeddings to second embeddings defined in a second latent space. A decoder neural network receives the second embeddings and decodes the second embeddings to generate beamformed radar data.
-
公开(公告)号：US20240302517A1
公开(公告)日：2024-09-12
申请号：US18272773
申请日：2022-01-18
申请人： Five AI Limited
发明人： Sina Samangooei , John Redford , Andrew Lawson , David Pickup
CPC分类号： G01S13/426 , G01S7/417 , G01S13/583 , G01S13/89
摘要： A computer-implemented method of perceiving structure in a radar point cloud comprises: generating a discretised image representation of the radar point cloud having (i) an occupancy channel indicating whether or not each pixel of the discretised image representation corresponds to a point in the radar point cloud and (ii) a Doppler channel containing, for each occupied pixel, a Doppler velocity of the corresponding point in the radar point cloud; and inputting the discretised image representation to a machine learning (ML) perception component, which has been trained extract information about structure exhibited in the radar point cloud from the occupancy and Doppler channels.
-
公开(公告)号：US12078714B2
公开(公告)日：2024-09-03
申请号：US17143147
申请日：2021-01-06
申请人： BDCM A2 LLC
IPC分类号： G01S13/44 , G01S7/41 , G01S13/931
CPC分类号： G01S13/4454 , G01S7/417 , G01S13/4427 , G01S13/931
摘要： Examples disclosed herein relate to a radar system and method of angular resolution refinement for use in autonomous vehicles. The method includes transmitting a radio frequency (RF) beam to a surrounding environment with a beamsteering radar system and receiving return RF beams from the surrounding environment. The method also includes generating radar data from the return RF beams and detecting objects from the radar data, and determining a direction of arrival of each of object and determining an angular distance between the objects. The method further includes initiating a guard channel detection based at least on the angular distance and determining gain amplitudes of the return RF beams, and determining a null between the objects from the gain amplitudes and resolving the objects as separate objects based at least on the determined null. The method also includes determining a refined direction of arrival of the objects based at least on the resolved objects.
-
4.发明授权公开(公告)号：US12072440B2
公开(公告)日：2024-08-27
申请号：US16497968
申请日：2018-03-28
申请人： SRI International
发明人： Girish Acharya , Douglas Bercow , John Brian Burns , Bradley J. Clymer , Aaron J. Heller , Jeffrey Lubin , Bhaskar Ramamurthy , David Watters , Aravind Sundaresan
CPC分类号： G01S7/415 , G01S7/412 , G01S7/417 , G01S13/584
摘要： An identification system includes a radar sensor configured to generate a time-domain or frequency-domain signal representative of electromagnetic waves reflected from one or more objects within a three-dimensional space over a period of time and a computation engine executing on one or more processors. The computation engine is configured to process the time-domain or frequency-domain signal to generate range and velocity data indicating motion by a living subject within the three-dimensional space. The computation engine is further configured to identify, based at least on the range and velocity data indicating the motion by the living subject, the living subject and output an indication of an identity of the living subject.
-
公开(公告)号：US12072437B2
公开(公告)日：2024-08-27
申请号：US17555414
申请日：2021-12-18
发明人： Joel Gross , Michael Hamilton
摘要： The present disclosure is directed to simulating patterns of reflected radar energy off of reference objects using motion data associated with these reference objects. This motion data may identify start times, start locations, end times, and end locations of a limited number reference objects in a set of discrete scenes. Each of these discrete scenes may also have a same time duration. Motion of these specific objects between a start time and an end time of each discrete scene may be interpolated. Once the locations of the objects are interpolated for a given scene, simulations may be performed to estimate the appearance of reflected radar signals that would be received by a radar apparatus. These simulations may identify patterns of reflected radar energy after radar signals have been emitted from the radar apparatus and these patterns may then be provided to train a machine learning apparatus.
-
公开(公告)号：US20240248170A1
公开(公告)日：2024-07-25
申请号：US18156828
申请日：2023-01-19
CPC分类号： G01S7/40 , G01S7/4013 , G01S7/4021 , G01S7/415 , G01S7/417 , G01S13/56 , G01S13/726 , G01S13/89
摘要： A method of operating a radar system includes: receiving a range-angle image (RAI) and a range-Doppler image (RDI) that are based on raw data from a radar sensor of the radar system; choosing, from a list of potential tasks, a task for the radar system to perform based at least on the RAI and the RDI; and modifying one or more parameters of the radar system in accordance with the chosen task for the radar system.
-
公开(公告)号：US12044796B2
公开(公告)日：2024-07-23
申请号：US17188106
申请日：2021-03-01
发明人： Xiangbing Feng , Yueqin Yu , Xueming Peng , Qi Chen
摘要： A method and apparatus for identifying behavior of a target, and a radar system applied to an automated driving scenario include receiving a radar echo signal from a target, processing the radar echo signal to obtain time-frequency domain data, processing the time-frequency domain data to obtain signal attribute feature data representing a first feature of a radar echo signal attribute and linear prediction coefficient (LPC) feature data representing a second feature of the radar echo signal, inputting the signal attribute feature data and the LPC feature data into a behavior identification model, and outputting behavior information of the target.
-
8.发明公开公开(公告)号：US20240230842A9
公开(公告)日：2024-07-11
申请号：US18487276
申请日：2023-10-16
发明人： Yeong Sang PARK , Kyoung-Wook Min , Jeong Dan CHOI
摘要： A method of filtering dynamic objects in radar-based ego-motion estimation includes converting measurement value at current time, measured by radar sensor, into point cloud, classifying the point cloud into points of a first object predicted as static object and points of a second object predicted as dynamic object, based on position value of dynamic object tracked at previous time, classifying the points of the first object into the points of the static object predicted as normal value and the points of the dynamic object predicted as outlier, based on outlier filtering algorithm, classifying the points of the second object into points of a candidate static object and points of a candidate dynamic object, based on velocity model of the static object, and tracking a position value of the dynamic object at current time, based on the points of the dynamic object and the points of the candidate dynamic object.
-
公开(公告)号：US20240192320A1
公开(公告)日：2024-06-13
申请号：US18582358
申请日：2024-02-20
申请人： NVIDIA Corporation
发明人： Tommi Koivisto , Pekka Janis , Tero Kuosmanen , Timo Roman , Sriya Sarathy , William Zhang , Nizar Assaf , Colin Tracey
IPC分类号： G01S7/41 , B60W50/00 , G01S7/48 , G01S13/86 , G01S13/931 , G01S17/931 , G06F16/35 , G06F18/21 , G06F18/214 , G06F18/23 , G06F18/2413 , G06N3/044 , G06N3/045 , G06N3/047 , G06N3/048 , G06N3/084 , G06N20/00 , G06V10/20 , G06V10/44 , G06V10/46 , G06V10/762 , G06V10/764 , G06V10/77 , G06V10/774 , G06V20/58
CPC分类号： G01S7/417 , B60W50/00 , G06F16/35 , G06F18/214 , G06F18/217 , G06F18/23 , G06F18/2414 , G06N3/044 , G06N3/045 , G06N3/084 , G06N20/00 , G06V10/255 , G06V10/454 , G06V10/46 , G06V10/762 , G06V10/764 , G06V10/7715 , G06V10/774 , G06V20/58 , G06V20/584 , G01S7/412 , G01S7/4802 , G01S13/867 , G01S2013/9318 , G01S2013/9323 , G01S17/931 , G06N3/047 , G06N3/048
摘要： In various examples, detected object data representative of locations of detected objects in a field of view may be determined. One or more clusters of the detected objects may be generated based at least in part on the locations and features of the cluster may be determined for use as inputs to a machine learning model(s). A confidence score, computed by the machine learning model(s) based at least in part on the inputs, may be received, where the confidence score may be representative of a probability that the cluster corresponds to an object depicted at least partially in the field of view. Further examples provide approaches for determining ground truth data for training object detectors, such as for determining coverage values for ground truth objects using associated shapes, and for determining soft coverage values for ground truth objects.
-
公开(公告)号：US20240184377A1
公开(公告)日：2024-06-06
申请号：US17786234
申请日：2021-06-24
发明人： Zongmin LIU , Li MA , Feng QU , Dongdong ZHANG , Wei LI , Xichao FAN , Junwei GUO , Biqi LI
摘要： The present disclosure provides an interactive control apparatus and an interactive system. The interactive control apparatus includes: an antenna array configured to transmit a radar signal and receive a reflected echo signal; a data processing assembly configured to determine, according to the radar signal and the echo signal, a body action and a corresponding control instruction, and output the control instruction to a terminal device; and a display assembly configured to display the determined body action and/or control instruction.
-
-
-
-
-
-
-
-
-
搜索结果
432 条记录 (耗时 0.035 秒)
