BAE Systems Information and Electronic Systems Integration Inc.
대리인 / 주소
Graybeal Jackson Haley LLP
인용정보
피인용 횟수 :
2인용 특허 :
20
초록▼
In an embodiment, a quantity smoother includes a first stage and a second stage. The first stage is operable to receive a sequence of raw samples of a quantity and to generate from the raw samples intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation re
In an embodiment, a quantity smoother includes a first stage and a second stage. The first stage is operable to receive a sequence of raw samples of a quantity and to generate from the raw samples intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples. The second stage is coupled to the first stage and is operable to generate from the intermediate samples resulting samples of the quantity, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples. For example, such a quantity smoother may be part of a target-ranging system on board a fighter jet, and may smooth an error in an estimated target range so that the fighter pilot may more quickly and confidently determine in his head a range window within which the target lies.
대표청구항▼
1. A quantity smoother, comprising: a first stage operable to receive a sequence of raw samples of a quantity and to generate from the raw samples intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; anda second
1. A quantity smoother, comprising: a first stage operable to receive a sequence of raw samples of a quantity and to generate from the raw samples intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; anda second stage coupled to the first stage and operable to generate from the intermediate samples resulting samples of the quantity, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples. 2. The apparatus of claim 1 wherein the first stage comprises a filter operable to: filter the raw samples; andgenerate the intermediate samples from the filtered samples. 3. The apparatus of claim 1 wherein the first stage comprises a filter operable to: median filter the raw samples; andgenerate the intermediate samples from the filtered samples. 4. The apparatus of claim 1 wherein the second stage comprises a curve fitter operable: to fit at least two of the intermediate samples to a polynomial; andto generate the resulting samples from the values of the polynomial at the sample times of the intermediate samples. 5. The apparatus of claim 1 wherein the second stage comprises a curve fitter operable: to fit at least two of the intermediate samples to a fifth-order polynomial; andto generate the resulting samples from the values of the polynomial at the sample times of the intermediate samples. 6. An apparatus, comprising: a parameter estimator operable to estimate a parameter from data related to the parameter;an error determiner operable to determine a raw error in the estimated parameter from information related to a level of accuracy of the data; andan error smoother operable to generate a smoothened error from the raw error. 7. The apparatus of claim 6 wherein: the parameter comprises a range from a ranging object to a ranged object; andthe data comprises at least one spatial coordinate of the ranged object. 8. The apparatus of claim 6 wherein the parameter estimator is operable to estimate the parameter according to a Kalman algorithm. 9. The apparatus of claim 6 wherein the error determiner is operable to determine the raw error in the estimated parameter in response to an accuracy value related to the accuracy of the estimated parameter. 10. The apparatus of claim 9, further comprising an accuracy determiner operable to determine the accuracy value from the accuracy of the data. 11. The apparatus of claim 9 wherein the accuracy value comprises a standard deviation associated with the estimated parameter. 12. The apparatus of claim 6 wherein the error smoother comprises: a filter operable to filter the raw error; anda curve fitter operable to fit the filtered error to a curve and to generate from the curve the smoothened error in the estimated parameter. 13. The apparatus of claim 12 wherein the filter comprises a median filter. 14. The apparatus of claim 12 wherein the curve fitter is operable to fit the filtered error to a curve that is defined by a fifth-order polynomial. 15. The apparatus of claim 6, further comprising: an antenna operable to receive a signal from an object; anda processor operable to derive from the signal at least one spatial coordinate of the object and to provide the spatial coordinate to the parameter estimator as the data. 16. The apparatus of claim 6, further comprising a display operable: to display a first value corresponding to the estimated parameter; andto display a second value corresponding to the smoothened error. 17. The apparatus of claim 6 wherein the parameter estimator is operable to estimate the parameter recursively from past values of the parameter. 18. A system, comprising: a vehicle; andan apparatus, comprising: a estimator operable to estimate a parameter related to a location of the vehicle from data related to the parameter;an error determiner operable to determine a raw error in the estimated parameter from information related to an error in the data; andan error smoother operable to generate a smoothened error from the raw error. 19. The system of claim 18 wherein the vehicle comprises an aircraft. 20. The system of claim 18 wherein: the parameter comprises a range from the vehicle to an object spaced from the vehicle; andthe data comprises at least one spatial coordinate of the object. 21. The system of claim 18 wherein the apparatus is located on the vehicle. 22. The system of claim 18, further comprising: an antenna disposed on the vehicle and operable to receive a signal from an object that is spaced from the vehicle; anda processor operable to derive from the signal at least one spatial coordinate of the object and to provide the spatial coordinate to the parameter estimator as the data. 23. The system of claim 18, further comprising an operator display disposed on the vehicle and operable: to display a first value corresponding to the estimated parameter; andto display a second value corresponding to the smoothened error. 24. A method, comprising: receiving a sequence of raw samples of a quantity;generating from the raw samples intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; andgenerating from the intermediate samples resulting samples of the quantity, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples. 25. A method, comprising: receiving a sequence of raw samples of an error in a parameter;generating from the raw samples intermediate samples of the error, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; andgenerating from the intermediate samples resulting samples of the error, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples. 26. A method, comprising: estimating a parameter from data related to the parameter;generating a raw error in the estimated parameter from information related to an accuracy of the estimated parameter; andsmoothing the raw error. 27. The method of claim 26 wherein: generating a raw error comprises generating a raw maximum error; andsmoothing the error comprises smoothing the raw maximum error. 28. The method of claim 26 wherein the information comprises a standard deviation associated with the estimated parameter. 29. The method of claim 26, further comprising: generating from the information a standard deviation associated with the estimated parameter; andwherein generating the raw error comprises generating the raw error in response to the standard deviation. 30. The method of claim 26 wherein smoothing the raw error comprises: median filtering the raw error;fitting the filtered error to a curve; andgenerating from the curve a smoothened error in the estimated parameter. 31. The method of claim 26, further comprising: wherein the parameter comprises a range between first and second objects;receiving a signal from the second object at the first object; andderiving from the signal at least one spatial coordinate of the second object, the at least one spatial coordinate composing at least a portion of the data. 32. The method of claim 26, further comprising displaying to a pilot a first value corresponding to the estimated parameter and a second value corresponding to the smoothened error. 33. The method of claim 26 wherein estimating the parameter comprises recursively estimating the parameter from previous values of the parameter. 34. A non-transitory computer-readable medium storing instructions that, when executed by a computing machine, cause the computing machine: to estimate a parameter from data related to the parameter;to generate a raw error in the estimated parameter from information related to an accuracy of the estimated parameter; andto smoothen the raw error. 35. A non-transitory computer-readable medium storing instructions that, when executed by a computing machine, cause the computing machine: to generate from a received sequence of raw samples of a quantity intermediate samples of the quantity, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; andto generate from the intermediate samples resulting samples of the quantity, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples. 36. A non-transitory computer-readable medium storing instructions that, when executed by a computing machine, cause the computing machine: to generate from a received sequence of raw samples of an error in a quantity intermediate samples of the error, the intermediate samples having a reduced level of fluctuation relative to the sequence of raw samples; andto generate from the intermediate samples resulting samples of the error, the resulting samples having a reduced level of fluctuation relative to the sequence of intermediate samples.
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이 특허에 인용된 특허 (20)
Tomasi Jean-Pierre (Les Molieres FRX), Aircraft position determining system.
McGraw,Gary A.; Frank,Robert J.; Peterson,Kenneth M.; Haendel,Richard S.; Zogg,Scott J. F., Relative navigation for precision rendezvous and station keeping using datalink signals.
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