Projectile launch point estimation from radar measurements

Nonlinear regression with an intercept is investigated and a new nonlinear regression algorithm is developed. The application area considered is ballistic trajectory determination from battlefield radar measurements. Specifically, the geolocation of an enemy artillery piece is pursued. Careful modelling of the nonlinear measurement situation at hand and the inclusion of an intercept parameter in the nonlinear regression shows a considerable improvement over conventional iterative least squares estimation when nonlinearity is dominant. Moreover, the estimation performance does not degrade from standard iterative least squares (ILS) in cases where the nonlinearity is weak compared to the measurement noise in the equation error, provided that the data record is sufficiently long.