초록 ▼

Systems and method for improving the presentation of sensed data (e.g., radar) by including a priori data. The a priori data is recast as if it were the output of a sensor. This allows the inclusion of the a priori data into an evidence grid that is combined with data from multiple types of sensors.

Systems and method for improving the presentation of sensed data (e.g., radar) by including a priori data. The a priori data is recast as if it were the output of a sensor. This allows the inclusion of the a priori data into an evidence grid that is combined with data from multiple types of sensors. Before the sensor data is combined into the evidence grid, the sensor data is aligned with the a priori data using an optimization algorithm. The optimization algorithm provides an optimum probability of a match between the sensor data and the a priori data by adjusting position or attitude associated with the sensor device. This removes any navigational errors associated with the sensor device data.

대표청구항 ▼

1. A method performed by a processing device located in a vehicle, the method comprising: a. receiving a first data set from at least a radar device corresponding to a first detection signal transmitted over a first spatial region based on initial location and attitude information of the radar devic

1. A method performed by a processing device located in a vehicle, the method comprising: a. receiving a first data set from at least a radar device corresponding to a first detection signal transmitted over a first spatial region based on initial location and attitude information of the radar device;b. determining a match probability between the first data set and previously stored a priori terrain and obstacle data based on the location and attitude information of the radar device and associated with the received first data set;c. if at least one of the determined match probability is not greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has not been met, adjusting at least one of the location or attitude information of the radar device and returning to b. based on the adjusted location or attitude information;d. if at least one of the determined match probability is greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has been met, saving the adjusted location or attitude information or the initial location and attitude information if no adjustment occurred;e. calculating the most likely occupancy values to cells in an evidence grid based on the first data set, the stored location and attitude information, and a second data set formed by representing the a priori terrain data as the output of a virtual sensor; andf. generating an output based on the most likely occupancy values. 2. The method of claim 1, wherein the evidence grid is three-dimensional. 3. The method of claim 1, wherein determining the match probability comprises calculating the probability that a first sub-region represented by a first cell reflects at least one detection signal of a plurality of detection signals. 4. The method of claim 3, wherein determining the match probability further comprises calculating the probability that the first sub-region represented by the first cell does not reflect at least one detection signal of the plurality of detection signals. 5. The method of claim 4, wherein determining the match probability further comprises calculating a first probability that each sub-region within a first bin of the first spatial region does not reflect at least one detection signal of the plurality of detection signals and a second probability that each sub-region within a first bin of a second spatial region does not reflect at least one detection signal of the plurality of detection signals. 6. The method of claim 5, wherein determining the match probability further comprises calculating a third probability that each sub-region within a second bin of the first spatial region reflects at least one detection signal of the plurality of detection signals and a fourth probability that each sub-region within a second bin of the second spatial region does not reflect at least one detection signal of the plurality of detection signals. 7. The method of claim 6, wherein determining the match probability further comprises: calculating a first product of the first probability and the third probability; andcalculating a second product of the second probability and the fourth probability. 8. The method of claim 7, wherein determining the match probability further comprises calculating a third product of the first and second products. 9. The method of claim 8, wherein determining the match probability further comprises calculating the maximum of the third product. 10. A vehicle comprising: a radar sensor configured to generate a first data set corresponding to a first detection signal transmitted over a first spatial region;memory configured to store a priori terrain and obstacle data;a positioning system configured to determine location and attitude information of the vehicle;a processing device coupled to the sensor, the processing device configured to: determine a match probability between the first data set and previously stored a priori terrain and obstacle data based on initial location and attitude information of the vehicle associated with the received first data set;adjust at least one of the location or attitude information of the vehicle and determine the match probability based on the adjusted location or attitude information, if at least one of the determined match probability is not greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has not been met;save the adjusted location or attitude information or the initial location and attitude information if no adjustment occurred, if at least one of the determined match probability is greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has been met;calculate the most likely occupancy values to cells in an evidence grid based on the first data set, the stored location and attitude information, and a second data set formed by representing the a priori terrain data as the output of a virtual sensor; andgenerate an output based on the most likely occupancy values; andan output device configured to output the generated output. 11. The vehicle of claim 10, wherein the evidence grid is three-dimensional. 12. The vehicle of claim 10, wherein the processing device determines the match probability by at least calculating the probability that a first sub-region represented by a first cell reflects at least one detection signal of a plurality of detection signals. 13. The vehicle of claim 12, wherein the processing device determines the match probability by at least further calculating the probability that the first sub-region represented by the first cell does not reflect at least one detection signal of the plurality of detection signals. 14. The vehicle of claim 13, wherein the processing device determines the match probability by at least further calculating a first probability that each sub-region within a first bin of the first spatial region does not reflect at least one detection signal of the plurality of detection signals and a second probability that each sub-region within a first bin of the second spatial region does not reflect at least one detection signal of the plurality of detection signals. 15. The vehicle of claim 14, wherein the processing device determines the match probability by at least further calculating a third probability that each sub-region within a second bin of the first spatial region reflects at least one detection signal of the plurality of detection signals and a fourth probability that each sub-region within a second bin of the a second spatial region does not reflect at least one detection signal of the plurality of detection signals. 16. The vehicle of claim 15, the processing determines the match probability by at least further: calculating a first product of the first probability and the third probability; andcalculating a second product of the second probability and the fourth probability. 17. The vehicle of claim 16, wherein the processing device determines the match probability by at least further calculating a third product of the first and second products. 18. The vehicle of claim 17, wherein the processing device determines the match probability by at least further calculating the maximum of the third product. 19. A system located in a vehicle, the system comprising: a means for receiving a first data set corresponding to a first radar detection signal transmitted over a first spatial region;a means for storing a priori terrain and obstacle data;a means for determining location and attitude information of the vehicle;a means for: determining a match probability between the first data set and previously stored a priori terrain and obstacle data based on initial location and attitude information of the vehicle associated with the received first data set;adjusting at least one of the location or attitude information of the vehicle and determine the match probability based on the adjusted location or attitude information, if at least one of the determined match probability is not greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has not been met;saving the adjusted location or attitude information or the initial location and attitude information if no adjustment occurred, if at least one of the determined match probability is greater than a predefined match probability threshold or a predefined threshold number of match probability determinations has been met;calculating the most likely occupancy values to cells in an evidence grid based on the first data set, the stored location and attitude information, and a second data set formed by representing the a priori terrain data as the output of a virtual sensor; andgenerating an output based on the most likely occupancy values; anda means for outputting the generated output.