Edge hardware online model learning and range estimation for autonomous aimpoint determination

A non-transitory computer readable medium comprising instructions that, when executed by a processor, cause the processor to:

• receive image data associated with a forward-looking perspective of a platform being directed to a target, the image data comprising image frames potentially containing the target;
• apply a first method of image processing to the image data, the first method of image processing being one that does not require the use of a target model, to finalize a pixel area in at least one image frame that matches characteristics associated with the target, to generate at least one track point corresponding to a distinctive portion of the target, and to provide an aimpoint associated with the target to a control system configured to control a position of at least a portion of the platform, relative to the target, and to bring the at least a portion of the platform onto an intercept course with the target;
• while iteratively applying the first method of image processing to the image data:
• store the at least one image frame that matches characteristics associated with the target thereby creating a reference image frame containing the target;
• determine the at least one track point on the target, the at least one track point comprising an invariant feature associated with the target;
• describe the at least one track point identified in the reference image frame using track point descriptors, the reference image frame, the at least one track point, and the track point descriptors comprising the target model;
• search for and update the at least one track point in a subsequent image frame;
• search for new track points in the subsequent image frame;
• and
• describe the new track points in the subsequent image frame using the track point descriptors and create an updated target model using the new track points;
• apply a second method of image processing to the image data, the second method of image processing comprising using the updated target model to track the target and update the aimpoint;
• and
• provide the updated aimpoint to the control system.

A seeker configured to seek a target, the seeker being configured to generate an aimpoint corresponding to a specific location on the target and comprising:

• an image sensor configured to capture image data associated with a forward-looking perspective of a platform being directed to the target, the image data comprising image frames potentially containing the target;
• and
• a processor in communication with the image sensor and with a non-transitory storage medium comprising instructions configured to cause the processor to:
• receive the image data;
• apply a first method of image processing to the image data, the first method of image processing being one that does not require the use of a target model, to finalize a pixel area in at least one image frame that matches characteristics associated with the target, to generate at least one track point corresponding to a distinctive portion of the target, and to generate the aimpoint associated with the target and provide the aimpoint to a control system configured to control a position of at least a portion of the platform, relative to the target, and to bring the at least a portion of the platform onto an intercept course with the target;
• while iteratively applying the first method of image processing to the image data:
• store the at least one image frame thereby creating a reference image frame containing the target;
• determine the at least one track point on the target, the at least one track point comprising an invariant feature associated with the target;
• describe the at least one track point identified in the reference image frame using track point descriptors, the reference image frame, the at least one track point, and the track point descriptors comprising the target model;
• search for and update the at least one track point in a subsequent image frame;
• search for new track points in the subsequent image frame;
• and
• describe the new track points in the subsequent image frame using the track point descriptors and create an updated target model using the new track points;
• apply a second method of image processing to the image data, the second method of image processing comprising using the target model to track the target and update the aimpoint;
• and
• estimate a range to the target and/or size of the target using only the image data, wherein said determination of the range to target and/or the size of target is based on a rate of reduction of target size using a linear regression problem,
• wherein the processor is configured to model a target angle in pixels (αpix) using range rate (ΔR), instantaneous field of view (IFOV), time to go (ttg), and cross-range projected dimension(s), as:
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• =
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• (
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• IFOV
• to use the model to solve for time to go, and then to combine the model with a range rate to determine the range to the target.