No abstract

Precision guidance filter design for a tactical missile with a strapdown seeker aided by low-cost strapdown sensors has been addressed in this paper. The low-cost strapdown sensors consist of an IMU with 3-axis accelerometers and gyroscopes, 3-axis magnetometers, and a barometer. Missile's position, velocity, attitude, and bias error of the barometer are considered as state variables. Since the state and measurement equations are highly nonlinear, we adopt UKF(Unscented Kalman Filter). The proposed guidance filter has a function of a navigation filter if target position error is not considered. In the case that the target position error is introduced, the proposed filter can effectively estimate the relative states of the missile to the true target. For specific engagement scenarios, we can observe that observability problems occur.

In an underwater environment, measurements regarding true targets and false targets (clutter) can be made. Therefore, a suitable data association method to exactly detect and track a target and an efficient track initiation method for judging tracks formed by the target should be selected in this environment. This paper attempts to propose a new data association method and track initiation method to detect and track targets more effectively. Also, the performance of the new method is tested in a series of Monte Carlo simulation runs and is compared with the existing data association and track initiation methods in a cluttered environment.

This paper proposes a new approach to reduce the target estimation error of the measurement angle, especially applied to the medium and long range surveillance radar. If the target has no maneuver and no change in heading direction for a certain time interval, the predicted angle of interacting multiple model(IMM) from the previous track information can be used to reduce the angle estimation error. The proposed method is simulated in 2 scenarios, a scenario with a non-maneuvering target and a scenario with a maneuvering target. The result shows that the new fusion solution(weighted IMM) with the predicted azimuth and the measured azimuth is worked properly in the two scenarios.

It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.