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US5267502A
Expired / Lapsed
US
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Weapons systems future muzzle velocity neural network
Assignee: SD-SCICON UK Ltd
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Filing: 1992-05-08
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Granted: 1993-12-07
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Expires: 2012-05-08
Abstract
Abstract In a device and method for predicting a future muzzle velocity of an indirect fire weapon 3, 7 means 9, 11 responsive to a measurement of muzzle velocity are adapted to implement an adaptive empirical prediction method to predict the future muzzle velocity. The invention also relates to an aiming system and method for an indirect-fire weapon 3, 7. The system comprises a muzzle velocity measuring device 5, and predictor means 9, 11 responsive to an output of the muzzle velocity measuring device 5 for determining a new elevation setting from the weapon. Preferably, the predictor means utilizes an adaptive empirical prediction method such as a Kalman Filter or neural network.
Inventors
- 👤 Christopher R. Gent
- 👤 Steven A. Bryant
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-02 22:09
CPC Classifications
F; F41; F41G; F41G3/00; F41G3/12; G; G01; G01S; G01S13/00; G01S13/02; G01S13/50; G01S13/58
Claims Analysis
Total Claims: 34
Claim 1
Independent Claim
50 words
A device for predicting a future muzzle velocity of an indirect-fire weapon, the device comprising: A) means for measuring muzzle velocity to produce a velocity output; and B) a neural network for implementing an adaptive empirical prediction method to predict the future muzzle velocity in response to the velocity output.
Claim 2
Independent Claim
50 words
A device for predicting a future muzzle velocity of an indirect-fire weapon, the device comprising: A) means for measuring muzzle velocity to produce a velocity output; and B) a neural network for implementing an adaptive empirical prediction method to predict the future muzzle velocity in response to the velocity output.
Claim 3
Dependent Claim
22 words
A device according to claim 1, further comprising means for utilizing future muzzle velocity to determine an elevation setting for the weapon.
Claim 4
Dependent Claim
18 words
A device according to claim 1, further comprising means responsive to relevant environmental, projectile and other calibration data.
Claim 5
Dependent Claim
16 words
A device according to claim 1, wherein the neural network is a recurrent multi-layer neural network.
Claim 6
Dependent Claim
52 words
A device according to claim 1, wherein the neural network self-organizes to represent: A) the nature of the errors in the normal muzzle velocity and their stochastic behavior over time; B) the relationship between these errors and the measurements identified above; and C) how the errors influence the prediction of muzzle velocity.
Claim 7
Dependent Claim
24 words
A device according to claim 5, wherein the neural network computes an estimate of the correction to be applied to the nominal muzzle velocity.
Claim 8
Dependent Claim
20 words
A device according to claim 1, wherein the neural network is implemented in combination with a first round prediction algorithm.
Claim 9
Independent Claim
37 words
A method of predicting a future muzzle velocity of an indirect-fire weapon, the method comprising measuring a muzzle velocity and using an adaptive empirical prediction method implemented as a neural network to predict the future muzzle velocity.
Claim 10
Independent Claim
37 words
A method of predicting a future muzzle velocity of an indirect-fire weapon, the method comprising measuring a muzzle velocity and using an adaptive empirical prediction method implemented as a neural network to predict the future muzzle velocity.
Claim 11
Dependent Claim
16 words
A method according to claim 8, wherein the neural network is a recurrent multi-layer neural network.
Claim 12
Dependent Claim
52 words
A method according to claim 8, wherein the neural network self-organizes to represent: A) The nature of the errors in the nominal muzzle velocity and their stochastic behavior over time; B) the relationship between these errors and the measurements identified above; and C) how the errors influence the prediction of muzzle velocity.
Claim 13
Dependent Claim
24 words
A method according to claim 10, wherein the neural network computes an estimate of the correction to be applied to the nominal muzzle velocity.
Claim 14
Dependent Claim
20 words
A method according to claim 8, wherein the neural network is implemented in combination with a first round prediction algorithm.
Claim 15
Dependent Claim
48 words
An aiming system for an indirect-fire weapon, the system comprising a muzzle velocity measuring device, and predictor means responsive to an output of the muzzle velocity measuring device for determining a new elevation setting for the weapon by implementing an adaptive empirical prediction method as a neural network.
Claim 16
Dependent Claim
48 words
An aiming system for an indirect-fire weapon, the system comprising a muzzle velocity measuring device, and predictor means responsive to an output of the muzzle velocity measuring device for determining a new elevation setting for the weapon by implementing an adaptive empirical prediction method as a neural network.
Claim 17
Dependent Claim
19 words
An aiming system according to claim 13, further comprising means responsive to relevant environmental, projectile and other calibration data.
Claim 18
Dependent Claim
17 words
An aiming system according to claim 13, wherein the neural network is a recurrent multi-layer neural network.
Claim 19
Dependent Claim
53 words
An aiming system according to claim 13, wherein the neural network self-organizes to represent: A) the nature of the errors in the nominal muzzle velocity and their stochastic behavior over time; B) the relationship between these errors and the measurements identified above; and C) how the errors influence the prediction of muzzle velocity.
Claim 20
Dependent Claim
25 words
An aiming system according to claim 16, wherein the neural network computes an estimate of the correction to be applied to the nominal muzzle velocity.
Claim 21
Dependent Claim
15 words
An aiming system according to claim 13, which aiming system is integrated with a weapon.
Claim 22
Dependent Claim
19 words
An aiming system according to claim 18, arranged to cooperate directly with a gun laying system of the weapon.
Claim 23
Dependent Claim
40 words
An aiming system according to claim 19, wherein the predicator means utilizes previous measured muzzle velocities to predict new muzzle velocity under the conditions for the next firing and also uses the predicted muzzle velocity to determine the elevation setting.
Claim 24
Dependent Claim
37 words
An aiming system according to claim 13, wherein the muzzle velocity measuring device is a Doppler radar device attached to the barrel of the weapon for measuring the velocity of a projectile as it leaves the barrel.
Claim 25
Dependent Claim
47 words
An aiming system according to claim 13, wherein an interface is also provided between the predictor means and the gun laying system used for setting the barrel, so that the quadrant elevation can be re-set automatically according to the new muzzle velocity predicted by the predictor means.
Claim 26
Dependent Claim
24 words
An aiming system according to claim 13, wherein the predictor means is responsive to initial values to enable the first firing to be effected.
Claim 27
Dependent Claim
54 words
An aiming system according to claim 13, wherein the predictor means comprises an electronic computer comprising: A) a memory for storing program, parameters and data; B) one or more input ports for receiving the necessary inputs; and C) one or more output ports for communicating the predicted muzzle velocities to a gun laying system.
Claim 28
Dependent Claim
21 words
An aiming system according to claim 13, wherein the neural network is implemented in combination with a first round prediction algorithm.
Claim 29
Independent Claim
56 words
A method of determining an elevation setting for an indirect-fire weapon, the method comprising firing the weapon and measuring the resultant muzzle velocity, and using the result of the measurement to make a prediction by using an adaptive empirical prediction method implemented as a neural network and thus determine a new elevation setting for the weapon.
Claim 30
Independent Claim
56 words
A method of determining an elevation setting for an indirect-fire weapon, the method comprising firing the weapon and measuring the resultant muzzle velocity, and using the result of the measurement to make a prediction by using an adaptive empirical prediction method implemented as a neural network and thus determine a new elevation setting for the weapon.
Claim 31
Dependent Claim
16 words
A method according to claim 26, wherein the neural network is a recurrent multi-layer neural network.
Claim 32
Dependent Claim
52 words
A method according to claim 26, wherein the neural network self-organizes to represent: A) the nature of the errors in the nominal muzzle velocity and their stochastic behavior over time; B) the relationship between these errors and the measurements identified above; and C) how the errors influence the prediction of muzzle velocity.
Claim 33
Dependent Claim
24 words
A method according to claim 28, wherein the neural network computes an estimate of the correction to be applied to the nominal muzzle velocity.
Claim 34
Dependent Claim
20 words
A method according to claim 26, wherein the neural network is implemented in combination with a first round prediction algorithm.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 1996-12-06 | 1997-06-07 | 1997-12-07 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2000-12-06 | 2001-06-07 | 2001-12-07 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2004-12-06 | 2005-06-07 | 2005-12-07 | $7700.00 | Window Closed / Lapsed |