System for modeling intelligent sensor selection and placement
View Patent ↗The present system for modeling intelligent sensor selection and placement takes signal and sensor information and calculates a statistical inference. As signal data passes through a series of processors, it is transformed by functions to account for signal emission, sensor reception, environmental factors, and noise. This produces a simulation of what the emitted signal would appear to be at a given sensor. The system may be used to select the most effective sensors for a given area or to determine the best sensor coverage for a given area.
1. A system for modeling performance of geographically distributed sensors, the system comprising:
a user interface configured to receive user defined Signal_Feature Attributes and user defined Directional Attributes;
an Instantiation Processor configured to instantiate Signal Objects, wherein each of said Signal Objects includes said Signal_Feature Attributes;
a Radiated_Signal Processor configured to receive said Signal Object and user defined Directional Attributes and to perform a Radiated_Signal Function to calculate Directional_Dependence Attributes for each of said Signal_Feature Attributes and update said Signal Object with said Directional_Dependence Attributes;
a Signal_Propagation Processor configured to receive said Directional_Dependence Attributes and environmental data, and performs a Signal_Propagation function to update said Signal Object with Vector_Signal Attributes for each of said Signal_Feature Attributes;
a Noise/Gain_Transfer Processor configured to receive said Vector_Signal Attributes and Sensor_Device Attributes and performs a Noise/Gain_Transfer Function to update said Signal Object with Scalar_Signal Attributes;
an Inference Processor configured to receive said Scalar_Signal Attributes and said Sensor_Device Attributes and performs an Inference Function to create a statistical model of signal propagation from which an inference can be drawn.
2. The system of claim 1 , wherein said Radiated_Signal Processor is configured to calculate the dependence of the signal on a direction of emission to create said Directional_Dependence Attributes.
3. The system of claim 1 , wherein said Directional Attributes include location of emitter, signal azimuth, and elevation angle relative to said emitter.
4. The system of claim 1 , wherein said Signal_Propagation Processor further creates one or more Vector_Signal Packets containing: (1) location data coordinates; and (ii) Vector_Signal Attributes, wherein each Vector_Signal Attribute represents a Signal_Feature Attribute associated with a location.
5. The system of claim 1 , wherein said Noise/Gain_Transfer Processor further creates a plurality of Noise_Signal Packets containing (i) a signals of interest partition and a background noise partition (ii) an offset value background noise, and (iii) power level value of each of said Signal_Feature Attributes expressed in scalar values.
6. The system of claim 5 , wherein said Noise/Gain_Transfer Processor is configured to apply a transfer function (gain) to each Vector_Signal Attributes.
7. The system of claim 5 , wherein said Noise/Gain_Transfer Processor is further configured to separately calculate a total power associated with said signal of interest partition.
8. The system of claim 5 , wherein said Noise/Gain_Transfer Processor is further configured to separately calculate a total power associated with background noise.
9. The system of claim 1 , wherein said environmental data is a geographical statistical model to provide an impact of terrain on signal propagation.
10. The system of claim 1 , wherein said environmental data is a weather statistical model to provide an impact of weather on signal propagation.
11. The system of claim 1 , wherein said environmental data is a geological statistical model to provide an impact of geology on signal propagation.
12. The system of claim 1 , wherein said Inference Processor is configured to calculate a statistical inference for at least one of a mean signal-to-noise ratio, a probability of detection, a target bearing, and location accuracy.
13. The system of claim 1 , wherein said Inference Processor component is further configured to create at least one inference Packet containing a statistical inference for at least one of a mean signal-to-noise ratio, a probability of detection, a target bearing, and location accuracy.
14. The system of claim 13 , wherein said Inference Processor is further configured to statistically combine all statistical inferences in said at least, one inference packet into a single inference.
15. The system of claim 1 , further including, a Sensor Database comprising a plurality of Sensor_Device Attributes.
16. The system of claim 1 , further including Signal_Feature Database comprising a plurality of Signal_Feature Attributes.
17. The system of claim 1 , further including a Relational Database comprising a plurality of emitters, a plurality of signals, and a plurality of Signal_Feature Attributes.