Study On Quick Prediction Of Artillery Location And Impact Points Based On Measurement Of Radar

Artillery locating and firing correction radar is a kind of the ground artillery radar, it is aimed at determining the enemy positions and amending our artillery’s shoot. Predicting the enemy positions and our artillery’s impact points accurately in time is crucial for the artillery locating and firing correction radar to realize its function. In this paper, from the view of ballistic prediction, approaches to predict artillery location and impact points based on measurement of radar is researched to provide the theoretical values for radar data processing.In view of that the conventional prediction of artillery location and impact points starts after the target tracking and measured data acquisition. It’s not real-time for radar data processing. In this paper, according to the amount of measured data, different methods have been taken to predict artillery location and impact points, which aims to make the target tracking be in parallel with trajectory predicting.In reconnaissance model, combined with the multi-model theory, parabolic approxi mation, least-squares approximation and nonlinear filtering have been taken to predict the artillery location in the process of measured data acquisition; in shooting amendin g model, predict the impact point depends on theoretic trajectory and measured data o f radar when the measured data’s amount is small, when the measured data increase, combine the theoretic trajectory and nonlinear filtering using weighting algorithm and multi-model theory to predict the impact point. Then, the simulations take the 120mm projectile for example. The result shows that, the approach to predict the artillery lo cation based on the multi-model theory can start predicting after the radar get two gr oups of data; the approach to predict the impact point based on the multi-model theor y can start predicting when the first measured data is got, meanwhile, the approach c an acquire more accurate results when the measured data is lack for the nonlinear filt ering algorithm; both of the approach can meet the requirement of real-time for radar data processing and provide values of engineering.