US 12,242,929 B2
Fano-based information theoretic method (FBIT) for design and optimization of nonlinear systems
John A. Malas, Kettering, OH (US); Patricia A. Ryan, Centerville, OH (US); and John A. Cortese, Reading, MA (US)
Assigned to United States of America as represented by the Secretary of the Air Force, Wright-Patterson AFB, OH (US)
Filed by Government of the United States as represented by the Secretary of the Air Force, Wright-Patterson AFB, OH (US)
Filed on Sep. 14, 2020, as Appl. No. 17/019,531.
Application 17/019,531 is a continuation in part of application No. 16/666,516, filed on Oct. 29, 2019.
Application 16/666,516 is a continuation in part of application No. 14/315,365, filed on Jun. 26, 2014, abandoned.
Claims priority of provisional application 61/914,429, filed on Dec. 11, 2013.
Prior Publication US 2021/0072348 A1, Mar. 11, 2021
Int. Cl. G01S 7/02 (2006.01); G01S 7/38 (2006.01); G06F 18/20 (2023.01); G06N 20/00 (2019.01); G06V 20/40 (2022.01)
CPC G06N 20/00 (2019.01) [G01S 7/021 (2013.01); G01S 7/38 (2013.01); G06F 18/295 (2023.01); G06V 20/41 (2022.01)] 11 Claims
OG exemplary drawing
 
1. A radar design and tuning system comprising:
a) a computer comprising an input/output controller, a random access memory unit, a hard drive memory unit, a unifying computer bus system and a central processing unit comprising an entropy computation processer, said input/output controller being configured to receive a digital signal from said instrumentation interface unit and transmit said digital signal to said central processing unit comprising said entropy computation processer; said central processing unit programmed to identify and characterize a component-level information loss in a nonlinear system configured to observe a target, the nonlinear system comprising a plurality of components with each component of the plurality having a control parameter, and the plurality of components of the nonlinear system being subject to at least one random input variable, via:
determining, for the nonlinear system, a true target state and a decision state, the true target and decision states being characterized in a Markovian channel model;
modeling settings of the at least one random input variable to create a plurality of distributions, wherein each distribution comprises values ranging from a theoretical maximum entropy to a theoretical minimum entropy;
calculating an entropy at each component of the plurality that is attributable to the respective control parameter wherein the entropy for each component of the plurality is directly related to an amount of uncertainty at each respective component of the plurality;
computing a mutual information between the true state and the decision state;
calculating the mutual information for each component of the plurality between the true target state and the respective component;
deriving, using Fano's inequality, a bound for a component probability of error for each component of the plurality using the mutual information associated with the respective component of the plurality;
determining the optimal design of components of the nonlinear system that minimize information loss, while maximizing information flow and mutual information; and
generating a design model for the nonlinear system to guide production;
b) an instrumentation interface unit, said instrumentation interface unit placing said computer in communication with a radar system; and
c) a communication device for communicating an output from said central processing unit to a human and/or an information storage device.