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US 8,138,965 B1Granted
Kinematic algorithm for rocket motor apperception
AssigneeLockheed Martin Corporation
InventorsThu-Van T. Luu, Jeffrey B. Boka
Life of this patent
Estimating the term…
Abstract
A method, Kinematic Algorithm for Rocket Motor Apperception (KARMA), for processing radar returns for identifying the type of a missile target includes generating tracks representing the missile, and applying the tracks to a set of plural template-based filters, each representing one missile hypothesis, to generate plural sets of missile states, one set for each hypothesis. The missile states are processed to generate kinematic parameter likelihood values (LLHs). The LLH values for each filter hypothesis are normalized and weighted. A weighted maximum likelihood value (WMLH) is calculated for each hypothesis. The correct hypothesis is deemed to be the one having the maximum WMLH, thus identifying the missile type.
Claims23
A method for identifying the type of a boosting missile, said method comprising:
- receiving radar returns from a boosting missile to generate a plurality of position measurements constituting a target missile track;
- providing a plurality of nominal kinematic missile rocket parameters including at least nominal missile speed, altitude, and flight path angle, said nominal kinematic missile parameters defining templates for each of a plurality of missile types;
- applying each of said nominal kinematic missile rocket parameters for each missile of said plurality of missile types to a separate boost phase filter of a set of plural boost phase filters;
- applying said target missile track to each boost phase filter of said set of plural boost phase filters, to generate a plurality of state estimates, one from each filter;
- and
- providing the output of each of said boost phase filters to at least one computer processor, said at least one computer processor performing the steps of:
- processing an output of each of said boost phase filters with the nominal kinematic missile rocket parameters applied to the boost phase filter, to generate a maximum likelihood value for each filter parameter and filter output;
- and
- selecting as a correct missile type that missile type associated with the filter having the maximum likelihood value.
6 more elements
A method for identifying a missile, said method comprising the steps of:
- receiving radar returns from a missile to generate a plurality of position measurements constituting a target missile track;
- providing a plurality of nominal kinematic missile parameters including at least nominal missile speed, altitude, and flight path angle, said nominal kinematic missile parameters defining templates for each missile type of a plurality of missile types;
- applying each of said nominal kinematic missile parameters for each missile type to a separate boost phase filter of a set of plural boost phase filters;
- applying said target missile track to each boost phase filter of said set of plural boost phase filters, to generate a plurality of state estimates, one for each missile type;
- and
- providing the output of each of said boost phase filters to at least one computer processor, said at least one computer processor performing the steps of:
- processing an output of each of said boost phase filters with the nominal kinematic missile parameters applied to the boost phase filter, to generate at least one maximum likelihood value for each filter parameter and missile type;
- for each of said maximum likelihood values, computing a sum across all said missile types;
- normalizing the likelihood values for all missile types to generate normalized likelihood values;
- selecting weighting parameters for each likelihood value, such that the sum of the weights for each likelihood value equals unity;
- determining a weighted maximum likelihood value for each missile type;
- and
- selecting as a correct missile type that missile type associated with the filter having the maximum likelihood value.
10 more elements
A system for identifying a missile, said system comprising:
- a non-transitory machine-readable medium upon which is stored instructions and
- a computer processor executing said instructions for performing the following steps:
- receiving radar returns from a boosting missile to generate a plurality of position measurements constituting a target missile track;
- providing a plurality of nominal kinematic missile rocket parameters including at least nominal missile speed, altitude, and flight path angle, said nominal kinematic missile parameters defining templates for each of a plurality of missile types;
- applying each of said nominal kinematic missile rocket parameters for each missile of said plurality of missile types to a separate boost phase filter of a set of plural boost phase filters;
- applying said target missile track to each boost phase filter of said set of plural boost phase filters, to generate a plurality of state estimates, one from each filter;
- processing an output of each of said boost phase filters with the nominal kinematic missile rocket parameters applied to the boost phase filter, to generate a maximum likelihood value for each filter parameter and filter output;
- and
- selecting as a correct missile type that missile type associated with the filter having the maximum likelihood value.
6 more elements
A method for identifying the type of a boosting missile, said method comprising:
- receiving radar returns from a boosting missile to generate a plurality of position measurements constituting a target missile track;
- providing a plurality of nominal missile rocket parameters for each of a plurality of missile types;
- applying each of said nominal missile rocket parameters for each missile of said plurality of missile types to a separate boost phase filter of a set of plural boost phase filters;
- applying said target missile track to each boost phase filter of said set of plural boost phase filters, to generate a plurality of state estimates, one from each filter;
- and
- providing the output of each of said boost phase filters to at least one computer processor, said at least one computer processor performing the steps of:
- processing an output of each of said boost phase filters with the nominal missile rocket parameters applied to the boost phase filter, to generate a maximum likelihood value for each filter parameter and filter output;
- and
- selecting as a correct missile type that missile type associated with the filter having the maximum likelihood value,
- wherein said step of processing the output of each of said boost phase filters with the nominal missile rocket parameters applied to the boost phase filter comprises the step of:
- calculating an altitude likelihood parameter for each filter hypothesis of a plurality of filter hypotheses.
8 more elements
A system for identifying a missile, said system comprising:
- a non-transitory machine-readable medium upon which is stored instructions, and
- a computer processor executing said instructions for performing the following steps:
- receiving radar returns from a boosting missile to generate a plurality of position measurements constituting a target missile track;
- providing a plurality of nominal missile rocket parameters for each of a plurality of missile type;
- applying each of said nominal missile rocket parameters for each missile of said plurality of missile types to a separate boost phase filter of a set of plural boost phase filters;
- applying said target missile track to each boost phase filter of said set of plural boost phase filters, to generate a plurality of state estimates, one from each filter;
- processing an output of each of said boost phase filters with the nominal missile rocket parameters applied to the boost phase filter, to generate a maximum likelihood value for each filter parameter and filter output;
- and
- selecting as a correct missile type that missile type associated with the filter having the maximum likelihood value,
- wherein said step of processing the output of each of said boost phase filters with the nominal missile rocket parameters applied to the boost phase filter comprises the step of:
- calculating an altitude likelihood parameter for each filter hypothesis of a plurality of filter hypotheses.
8 more elements
Dependencies are inferred from the claim text.