Non-resolved target detection system and methods
AssigneeRaytheon Company
InventorDarin C. Koblick
Life of this patent
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Abstract
Systems and methods are provided for modeling non-resolved object detection performance of sensor systems. An exemplary method includes: receiving a first data from or associated with a plurality of sensors; creating, using the first data, a plurality of models for each of the sensors; calculating, using the models and the first data, signal-to-ratio (SNR) values for the sensors against a target; creating, using the SNR values, a plurality of probability of detection models for each of the sensors, wherein one of the probability of detection models is a quantum illumination probability of detection model; and determining, using the detection models, non-resolved target detection performance of each of the sensors.
Claims18
A system for modeling non-resolved object detection performance of sensor systems, the system comprising one or more computing device processors;
- and
- one or more computing device memories, coupled to the one or more computing device processors, the one or more computing device memories storing instructions executed by the one or more computing device processors, wherein the instructions are configured to:
- receive a first data from or associated with at least one RADAR sensor, quantum RADAR sensor, or Electro-Optical and Infrared (EOIR) sensor;
- create, using the first data, a plurality of detailed illumination models for each of the sensors;
- calculate, using the detailed illumination models and the first data, signal-to-ratio (SNR) values for the sensors against a target using a target signal, localized standard deviation of background noise, and a received intensity point on a single frame at a center pixel location;
- create, using the SNR values, a plurality of probability of detection models for each of the sensors, wherein at least one of the probability of detection models is a quantum illumination probability of detection model, noise from cloud clutter model that characterizes noise induced from cloud clutter, spatial match filter and velocity matched filtering model that keeps a peak location of a point source unchanged, EOIR atmospheric attenuation that determines a loss of signal propagating through the atmosphere, and a quantum radar sensor model that produces a quantum illumination optimal receiver probability of detection;
- determine, using the detection models, non-resolved target detection performance of each of the EOIR sensor;
- and
- display, via a user interface, sensor properties and visual performance metrics thereby improving an operator's understanding of an object detected and its surroundings.
A method for modeling non-resolved object detection performance of sensor systems, the method comprising:
- receiving a first data from or associated with at least one RADAR sensor, quantum RADAR sensor, or Electro-Optical and Infrared (EOIR) sensor;
- creating, using the first data, a plurality of detailed illumination models for each of the sensors;
- calculating, using the detailed illumination models and the first data, signal-to-ratio (SNR) values for the sensors against a target using a target signal, localized standard deviation of background noise, and a received intensity point on a single frame at a center pixel location;
- creating, using the SNR values, a plurality of probability of detection models for each of the sensors, wherein at least one of the probability of detection models is a quantum illumination probability of detection model, noise from cloud clutter model that characterizes noise induced from cloud clutter, spatial match filter and velocity matched filtering model that keeps a peak location of a point source unchanged, EOIR atmospheric attenuation that determines a loss of signal propagating through the atmosphere, and a quantum radar sensor model that produces a quantum illumination optimal receiver probability of detection;
- determining, using the detection models, non-resolved target detection performance of each of the sensors;
- and
- displaying, via a user interface, sensor properties and visualize performance metrics thereby improving an operator's understanding of an object detected and its surroundings.
A non-transitory computer-readable storage medium storing instructions which when executed by a computer cause the computer to perform a method for modeling non-resolved object detection performance of sensor systems, the method comprising:
- receiving a first data from or associated with at least one RADAR sensor, quantum RADAR sensor, or Electro-Optical and Infrared (EOIR) sensor;
- creating, using the first data, a plurality of detailed illumination models for each of the sensors;
- calculating, using the detailed illumination models and the first data, signal-to-ratio (SNR) values for the sensors against a target using a target signal, localized standard deviation of background noise, and a received intensity point on a single frame at a center pixel location;
- creating, using the SNR values, a plurality of probability of detection models for each of the sensors, wherein at least one of the probability of detection models is a quantum illumination probability of detection model, noise from cloud clutter model that characterizes noise induced from cloud clutter, spatial match filter and velocity matched filtering model that keeps a peak location of a point source unchanged, EOIR atmospheric attenuation that determines a loss of signal propagating through the atmosphere, and a quantum radar sensor model that produces a quantum illumination optimal receiver probability of detection;
- determining, using the detection models, non-resolved target detection performance of each of the sensors;
- and
- displaying, via a user interface, sensor properties and visualize performance metrics thereby improving an operator's understanding of an object detected and its surroundings.
Dependencies are inferred from the claim text.