Covert ranging method and system

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• (f) changing said predicted target data set in response to said system error;
• and
• (g) constraining said active target data set by a plurality of penalty functions upon determining that a certain aspect of said active target data set exceeds a predetermined limit, said plurality of penalty functions including a maximum acquisition range penalty associated with a maximum acquisition range aspect of said active target data set.

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• (f) changing said predicted target data set in response to said system error;
• (g) constraining said active target data set by a plurality of penalty functions upon determining that a certain aspect of said active target data set exceeds a predetermined limit;
• and
• (h) using said plurality of penalty functions to associate small weights with said active target data set when a predetermined aspect of said active target set falls within said predetermined limit and associated large weights with said active target data set when said predetermined aspect falls outside said predetermined limit.

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• (f) changing said predicted target data set in response to said system error;
• and
• (g) constraining said active target data set by a plurality of penalty functions upon determining that a certain aspect of said active target data set exceeds a predetermined limit, said plurality of penalty functions including a speed penalty associated with a speed measurement aspect of said active target data set.

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• (f) changing said predicted target data set in response to said system error;
• (g) limiting said changing step by a perturbation magnitude, said perturbation magnitude associated with said system error;
• and
• (h) limiting said perturbation magnitude using a linear search procedure.

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• (f) changing said predicted target data set in response to said system error;
• and
• (g) limiting said changing step by a perturbation direction, said perturbation direction associated with said system error.

A method for covertly determining and predicting target data relative to a predetermined position, comprising the steps of:

• (a) passively sensing a target to produce a passive target data set, said passive target data set including early sighting data for advising of a flight path of said target;
• (b) relating said passive target data set to said predetermined position to produce a transformed passive data set;
• (c) comparing said transformed passive data set to a predicted target data set to generate a measurement error;
• (d) actively sensing said target for a minimally detectable period of time to produce an active target data set;
• (e) relating said active target data set to said measurement error to produce a system error;
• and
• (f) changing said predicted target data set in response to said system error.

A system for covertly determining and predicting target data relative to a predetermined position, comprising:

• a passive sensor for passively sensing a target to produce a passive target data set;
• coordinate transformation circuitry for relating said passive target data set to said predetermined position to produce a transformed passive data set;
• comparison circuitry for comparing said transformed passive data set to a predicted target data set and thereby generating a measurement error;
• an active sensor for actively sensing said target for a minimally detectable period of time to produce an active target data set;
• system error circuitry for relating said active target data set to said measurement error to produce a system error;
• and
• perturbation circuitry for changing said predetermined target data set in response to said system error.