Correlation/estimation reporting engagement system and method
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
F41G-007/22
F41G-007/00
출원번호
US-0026661
(2013-09-13)
등록번호
US-9285190
(2016-03-15)
발명자
/ 주소
Boardman, Jonathan A.
Boka, Jeffrey B.
Patel, Naresh R.
출원인 / 주소
Lockheed Martin Corporation
대리인 / 주소
Howard IP Law Group, PC
인용정보
피인용 횟수 :
1인용 특허 :
17
초록▼
A system and method for performing correlation processing for identifying an object of interest in a cloud of remote objects of different types comprises receiving RF and IR measurement data including rotational, translational bias and noise errors and determining and removing biases by minimizing a
A system and method for performing correlation processing for identifying an object of interest in a cloud of remote objects of different types comprises receiving RF and IR measurement data including rotational, translational bias and noise errors and determining and removing biases by minimizing a weighted distance metric. Correlation pairing metrics are then determined according to a maximum likelihood criteria. This method produces a correlation solution that minimizes the effects of biases and random noise while accounting for the statistical properties of the parameters being estimated.
대표청구항▼
1. A method for selecting an object of interest in a cloud of objects of lesser interest comprising: obtaining object positional data from at least one RF sensor and at least one IR sensor;processing, by a processor of an electromagnetic/optical correlator, the positional data to generate a dimensio
1. A method for selecting an object of interest in a cloud of objects of lesser interest comprising: obtaining object positional data from at least one RF sensor and at least one IR sensor;processing, by a processor of an electromagnetic/optical correlator, the positional data to generate a dimensional representation in a common reference frame;combining, by said electromagnetic/optical correlator processor, the RF and IR positional data to determine translational bias and angular misalignment errors associated with the RF and IR positional data;defining, by said electromagnetic/optical correlator processor, a weighted distance metric based on sensor measurement uncertainties;determining, by said correlation processor, bias estimates based on the distance metric; anddetermining, by said electromagnetic/optical correlator processor, correlation components for each combination of RF and IR objects using the determined bias estimates for generating RF/IR correlation matrix data for input to an object selection process. 2. The method of claim 1, wherein the step of processing the positional data to generate a dimensional representation in a common reference frame comprises projecting the RF sensor data onto the IR sensor line of sight (LOS) coordinate frame. 3. The method of claim 1, wherein the step of combining the RF and IR measurements to determine translational bias and angular misalignment errors comprises determining the difference between the RF and IR positional data to obtain measurement errors. 4. The method of claim 3, further comprising subtracting the bias estimates from the obtained measurement errors. 5. The method of claim 4, further comprising determining state estimates associated with radar bias and IR rotational misalignment estimates according to the weighted distance metric. 6. The method of claim 5, wherein the weighted distance metric is: |d|2={right arrow over (ε)}TW−1{right arrow over (ε)}+{circumflex over (β)}TR−1{circumflex over (β)}+{circumflex over (Γ)}TV−1{circumflex over (Γ)}wherein W, R and V are weight matrices representative of the measurement noise covariance, radar bias covariance and the IR sensor rotational misalignment covariance. 7. A system for identifying an object of interest in a cloud of remote objects of different types, where the number of object types is no greater than X, said system comprising: an RF sensor observing said cloud, and configured to generate RF signals representing RF tracked object data for at least some of the objects of said cloud;an electromagnetic discriminator including a computer processor coupled to said RF sensor and configured to compute the probability of each RF tracked object being one of the X possible object types;an optical sensor observing at least portions of said cloud, and configured to generate infrared (IR) optical signals representing IR tracked object data for at least some objects of said cloud;an optical discriminator including a computer processor configured to compute the probability of each IR tracked object being one of the X possible object types;an electromagnetic/optical correlator configured to determine the probability that the ith electromagnetic object is correlated or matched with the jth optical object, the correlator including a computer processor configured to: generate an electromagnetic/optical correlation matrix by processing RF and IR positional data to generate a dimensional representation in a common reference frame;combine RF and IR measurements to determine translational bias and angular misalignment errors associated with the RF and IR measurements;define a weighted distance metric based on sensor measurement uncertainties; determining bias estimates based on the distance metric; anddetermine correlation components for each combination of RF and IR objects using the determined bias estimates for generating RF/IR correlation matrix data for input to an object selection process. 8. The system of claim 7, wherein said electromagnetic/optical correlator is further configured to determine the probability of correlation pairing according to a maximum likelihood criteria. 9. The system of claim 8, wherein said electromagnetic/optical correlator is further configured to combine the RF and IR measurements to determine translational bias and angular misalignment errors by determining the difference between the RF and IR measurements to obtain measurement errors. 10. The system of claim 7, wherein said electromagnetic/optical correlator is further configured to generate a dimensional representation in a line of sight (LOS) reference frame by projecting the RF sensor data onto the IR sensor LOS coordinate frame. 11. The system of claim 7, wherein said electromagnetic/optical correlator is further configured to subtract the bias estimates from the obtained measurement errors. 12. Apparatus for providing correlation data for object selection and target intercept comprising: a data storage device storing object positional data from at least one RF sensor and at least one IR sensor measurements;one or more computer processors in communication with the data storage device including an electromagnetic/optical correlator processor; anda program memory, coupled to the one or more computer processors, storing on a non-transitory computer-readable medium program instruction steps for execution by the one or more computer processors, the program instructions, when executed by the one or more computer processors, causing the one or more computer processors to: process the positional data by said electromagnetic/optical correlator processor to generate a dimensional representation in a common reference frame;combine in said electromagnetic/optical correlator processor, the RF and IR measurements to determine translational bias and angular misalignment errors associated with the RF and IR measurements;define in said electromagnetic/optical correlator processor, a weighted distance metric based on sensor measurement uncertainties;determine in said electromagnetic/optical correlator processor, bias estimates based on the distance metric; anddetermine in said electromagnetic/optical correlator processor correlation components for each combination of RF and IR objects using the determined bias estimates for generating RF/IR correlation matrix data for input to an object selection process. 13. The apparatus of claim 12, wherein the program instructions, when executed by the electromagnetic/optical correlator processor, further cause the one or more computer processors to: generate a dimensional representation in a common reference frame that comprises projecting the RF sensor data onto the IR sensor LOS coordinate frame. 14. The apparatus of claim 12, wherein the program instructions, when executed by the electromagnetic/optical correlator processor, further cause the electromagnetic/optical correlator processor to combine the RF and IR measurements to determine translational bias and angular misalignment errors by determining the difference between the RF and IR measurements to obtain measurement errors. 15. The apparatus of claim 12, wherein the program instructions, when executed by electromagnetic/optical correlator processor, further cause the electromagnetic/optical correlator processor to subtract the bias estimates from the obtained measurement errors. 16. The apparatus of claim 15, wherein the program instructions, when executed by the electromagnetic/optical correlator processor, further cause the electromagnetic/optical correlator processor to determine state estimates associated with radar bias and IR rotational misalignment estimates according to the weighted distance metric. 17. The apparatus of claim 16, wherein the weighted distance metric is: |d|2={right arrow over (ε)}TW−1{right arrow over (ε)}+{circumflex over (β)}TR−1{circumflex over (β)}+{circumflex over (Γ)}TV−1{circumflex over (Γ)} wherein W, R and V are weight matrices representative of the measurement noise covariance, radar bias covariance and the IR sensor rotational misalignment covariance.
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이 특허에 인용된 특허 (17)
Bobinchak, James; Hewer, Gary, Apparatus and method for cooperative multi target tracking and interception.
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