# US 11,029,130 B2 · Mission planning for weapons systems > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,029,130 B2 - Document ID: US11029130B2 - Status: Granted - Kind: B2 - Application number: 16/614,857 - Filed: 2018-05-17 - Published: 2020-07-02 - Granted: 2021-06-08 - Earliest claimed: 2017-05-25 - Assignees: Mbda UK Limited - Applicants: Mbda UK Limited - Inventors: Gareth Stanley Rees; Andrew Philip Walls; Alex Martin Robinson; Stephen Vincent Sargent; Nathan Rees Potter; Leigh Moody - Web page: https://patentgrep.com/patent/US11029130B2 ## CPC - F41G 7/007: {Preparatory measures taken before the launching of the guided missiles} - F41G 7/002: {target simulators} - F41G 7/224: {Deceiving or protecting means (jamming or anti-jamming of radio-wave systems in general G01S7/36, G01S7/38; defense installations in general F41H11/02; chaff dispensers F42B12/70)} - F41H 11/02: Anti-aircraft or anti-guided missile {or anti-torpedo} defence installations or systems (cartridges or missiles for producing smoke or for dispensing radar chaff or infrared material F42B5/15, F42B12/48, F42B12/70; {informative reference: details of radar or sonar systems G01S7/00; jamming or electronic countermeasures G01S7/38, G01S7/495, H04K3/00}) - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - F41G: WEAPON SIGHTS; AIMING (optical aspects thereof G02B) - F41H: ARMOUR; ARMOURED TURRETS; ARMOURED OR ARMED VEHICLES; MEANS OF ATTACK OR DEFENCE, e.g. CAMOUFLAGE, IN GENERAL - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract A mission planning method for use with a weapon is disclosed. The method comprises: obtaining a first training data set describing the performance of the weapon; using the first training data set and a Gaussian Process (GP) or Neural Network to obtain a first surrogate model giving a functional approximation of the performance of the weapon; and providing the first surrogate model to a weapons system for use in calculating a performance characteristic of the weapon during combat operations. ## Claims ### Claim 1 A mission planning method for use with a weapon, the method comprising the steps of: obtaining a first training data set describing the performance of the weapon; using the first training data set and a Gaussian Process (GP) to obtain a first surrogate model giving a functional approximation of the performance of the weapon, the Gaussian process comprising using a covariance function to calculate a set of hyper-parameters and a set of weighted values; and providing the first surrogate model to a weapons system for use in calculating a performance characteristic of the weapon during combat operations. ### Claim 2 (depends on 1) A mission planning method according to claim 1, wherein the surrogate model further comprises a set of inducing points. ### Claim 3 (depends on 1) A mission planning method according to claim 1, wherein the Gaussian Process algorithm used is the Fully Independent Training Conditional (FITC) algorithm. ### Claim 4 (depends on 1) A mission planning method according to claim 1, further comprising calculating a performance characteristic of the weapon during combat operations using the surrogate model. ### Claim 5 (depends on 4) A mission planning method according to claim 4, further comprising initiating launch of the weapon in dependence on the performance characteristic so calculated. ### Claim 6 (depends on 1) A mission planning method according to claim 1, the method comprising the steps of: obtaining a second training data set describing the performance of the weapon in a second, different, parameter space to the first training data set; using the second training data set and a Gaussian Process (GP) or Neural Network to obtain a second, different, surrogate model giving a functional approximation of the performance of the weapon in the second parameter space; providing the first and second surrogate models to a weapons system for use in calculating a performance characteristic of the weapon during combat operations. ### Claim 7 (depends on 6) A mission planning method according to claim 6, further comprising, during combat operations, selecting the first or second surrogate model in dependence on the current parameters and using the surrogate model so selected to calculate a performance characteristic of the weapon. ### Claim 8 (depends on 1) A mission planning method according to claim 1, wherein the weapon is a missile. ### Claim 9 (depends on 1) A mission planning method according to claim 1, wherein the weapon system comprises a weapons platform and the weapons platform is an aircraft, ship or land vehicle. ### Claim 10 (depends on 1) A mission planning method according to claim 1, wherein the performance characteristic is the Launch Success Zone (LSZ), the Launch Acceptable Region (LAR), the footprint, the aerodynamic drag of the weapon and/or the trajectory of an enemy weapon. ### Claim 11 A weapons system comprising a processor programmed with software configured to calculate a performance characteristic of a weapon of the weapons system during combat operations using a functional approximation of the performance of the weapon, said functional approximation comprising a surrogate model produced using a Gaussian Process, the Gaussian process comprising using a covariance function to calculate a set of hyper-parameters and a set of weighted values. ### Claim 12 (depends on 11) A weapons system according to claim 11, further comprising a launcher, and wherein the launcher comprises the processor. ### Claim 13 (depends on 11) A weapon configured for use as the weapon of the weapons system of claim 11, wherein the weapon comprises the processor. ### Claim 14 (depends on 11) A weapons system according to claim 11, further comprising a weapons platform, wherein the processor is part of the command and control system of the weapons platform. ### Claim 15 A computer software product for loading onto a processor associated with a weapons system, wherein the software product is configured to calculate a performance characteristic of a weapon of the weapons system during combat operations using a functional approximation of the performance of the weapon, said functional approximation comprising a surrogate model produced using a Gaussian Process, the Gaussian process comprising using a covariance function to calculate a set of hyper-parameters and a set of weighted values. ### Claim 16 (depends on 15) A computer software product according to claim 15, wherein the surrogate model is produced using a Gaussian Process and the surrogate model comprises a covariance function, a set of hyper-parameters and a set of weighted values.