Object fusion system of multiple radar imaging sensors

US9255988B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9255988-B2
Application numberUS-201414156681-A
CountryUS
Kind codeB2
Filing dateJan 16, 2014
Priority dateJan 16, 2014
Publication dateFeb 9, 2016
Grant dateFeb 9, 2016

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  1. Title

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Abstract

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A method of detecting and tracking objects using multiple radar sensors. Objects relative to a host vehicle are detected from radar data generated by a sensing device. The radar data includes Doppler measurement data. Clusters are formed, by a processor, as a function of the radar data. Each cluster represents a respective object. Each respective object is classified, by the processor, as stationary or non-stationary based on the Doppler measurement data of each object and a vehicle speed of the host vehicle. Target tracking is applied, by the processor, on an object using Doppler measurement data over time in response to the object classified as a non-stationary object; otherwise, updating an occupancy grid in response to classifying the object as a stationary object.

First claim

Opening claim text (preview).

What is claimed is: 1. A method of detecting and tracking objects using multiple radar sensors comprising: detecting objects relative to a host vehicle from radar data generated by a sensing device, the radar data including Doppler measurement data; forming clusters, by a processor, as a function of the radar data, each cluster representing a respective object; classifying, by the processor, each respective object as stationary or non-stationary based on the Doppler measurement data of each object and a vehicle speed of the host vehicle; and applying target tracking, by the processor, on an object using Doppler measurement data over time in response to the object classified as a non-stationary object, otherwise, updating an occupancy grid in response to classifying the object as a stationary object. 2. The method of claim 1 wherein forming clusters comprises the following steps: identifying each point detected by the first sensing device, each point including a location position and an associated range relative to the host vehicle; assigning each point as a separate cluster; comparing neighboring points and merging neighboring points into a same cluster if similarity metrics between the neighboring points is within a similarity threshold. 3. The method of claim 2 further comprising the step of indexing each point using a k-d tree. 4. The method of claim 3 further comprising the step of indexing each point using a hash look-up tree. 5. The method of claim 3 wherein the similarity metrics includes Doppler measurement data. 6. The method of claim 1 wherein classifying each respective object as stationary or non-stationary comprises the following steps: identifying a velocity for each point within a cluster; identifying a unit vector for each point with the cluster; determining a range rate residue value for each point within the cluster; determining that the cluster is a stationary cluster if a predetermined percent of the range rate residue values are within a residue threshold; otherwise determining that the cluster is a dynamic cluster. 7. The method of claim 6 wherein the velocity of each point within the cluster is determined by the following equation: ν xi =y i ω H −ν H ν yi =−x i ω H where ν xi is a lateral velocity of an i th point, ν yi is a longitudinal velocity of the i th point, y i is a longitudinal coordinate relative to the vehicle of the i th point, x i is a latitudinal coordinate relative to the vehicle of the i th point, ω H is yaw rate, and, ν H is a speed. 8. The method of claim 7 wherein the range rate residue value is determined by the following equation: ε i =|{right arrow over (ν)} i ·{right arrow over (n)} i −d i | where ν i is the determined speed, and n i is a unit vector. 9. The method of claim 6 wherein the predetermined percentage is substantially 80%. 10. The method of claim 1 wherein applying tracking comprises the following steps: determining an orientation and position of the cluster at a previous instance of time using radar data; determining an orientation and position of the cluster at a current instance of time using radar data; determining a translation velocity in response to the orientation and position of the cluster at the previous and next instance of time; updating an object tracking model of the cluster at the current instance of time utilizing the translation velocity. 11. The method of claim 10 wherein the transformation velocity is determined by the following equation: v = arg ⁢ ⁢ min v ⁢ ∑ kj ⁢ ⁢ a kj (  s k - T v ⁡ ( m j )  2 σ 1 +  d k - v j · n j  2 σ 2 ) where s k is a radar point, m j is a model point, T ν(n) is an operator applying rigid motion during ν during Δt for a point x, α kj is the probability that radar point s k is associated with model point m j (i.e., the measurement of the model point m j ), d k is the Doppler measurement of the radar point s k , n j is the unit direction from the radar center to the model point m j , and ν j is the related velocity for the model point m j . 12. The method of claim 11 wherein the related velocity for the model is determined by the following formula: ν j =ν t +( m j −o )×ω where (ν t , ω) are translation and angular velocities in ν. 13. The method of claim 12 wherein the object tracking model for the current instance of time is updated as a function of the transformation velocity determined for a current instance of time. 14. The

Assignees

Inventors

Classifications

  • of land vehicles · CPC title

  • in the front of the vehicles · CPC title

  • in the back of the vehicles · CPC title

  • Identification of targets based on measurements of movement associated with the target · CPC title

  • Combination of several spaced transmitters or receivers of known location for determining the position of a transponder or a reflector (G01S13/874 takes precedence) · CPC title

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What does patent US9255988B2 cover?
A method of detecting and tracking objects using multiple radar sensors. Objects relative to a host vehicle are detected from radar data generated by a sensing device. The radar data includes Doppler measurement data. Clusters are formed, by a processor, as a function of the radar data. Each cluster represents a respective object. Each respective object is classified, by the processor, as stati…
Who is the assignee on this patent?
Gm Global Tech Operations Inc
What technology area does this patent fall under?
Primary CPC classification G01S13/66. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Feb 09 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).