Composite Guidance for Impact Angle Control Against Higher Speed Targets

In the literature, the impact angle control problem has been addressed mostly against lower speed or stationary targets. However, in the current defense scenario, targets of much higher speeds than interceptors are a reality. Moreover, approaching a higher speed target from a specified angle is important for effective seeker acquisition and enhanced warhead effectiveness. This paper proposes a composite proportional navigation guidance law using a combination of the standard proportional navigation and the recently proposed retroproportional navigation guidance laws for intercepting higher speed nonmaneuvering targets at specified impact angles in three-dimensional engagements. An analysis of the set of achievable impact angles by the composite proportional navigation guidance law is presented. It is shown that there exists an impulse bias that, when added to the composite proportional navigation guidance command, expands this set further by reversing the direction of the line-of-sight angular rotation vector. A bound on the magnitude of the bias is also derived. Finally, an implementation of this impulse bias, in the form of a series of pulses, is proposed and analyzed. Simulation results are also presented to support the analysis.

Composite Guidance for Impact Angle Control Against Higher Speed Targets

In the literature, the impact angle control problem has been addressed mostly against lower speed or stationary targets. However, in the current defense scenario, targets of much higher speeds than interceptors are a reality. Moreover, approaching a higher speed target from a specified angle is important for effective seeker acquisition and enhanced warhead effectiveness. This paper proposes a composite proportional navigation guidance law using a combination of the standard proportional navigation and the recently proposed retroproportional navigation guidance laws for intercepting higher speed nonmaneuvering targets at specified impact angles in three-dimensional engagements. An analysis of the set of achievable impact angles by the composite proportional navigation guidance law is presented. It is shown that there exists an impulse bias that, when added to the composite proportional navigation guidance command, expands this set further by reversing the direction of the line-of-sight angular rotation vector. A bound on the magnitude of the bias is also derived. Finally, an implementation of this impulse bias, in the form of a series of pulses, is proposed and analyzed. Simulation results are also presented to support the analysis.

A Nonlinear Guidance Law for Impact Time Control

This paper discusses the problem of impact time control of an interceptor against a stationary target. A nonlinear guidance law is proposed with the interceptor heading angle variation as a function of the range to target. Closed-form expressions for the design parameters are derived for an exact analysis of the impact time. A feedback form of the guidance law is presented for addressing realistic implementation in the presence of autopilot lag. Using the closed-form expressions of the impact time, a cooperative guidance scheme is presented for simultaneous impact in a salvo attack. Extensive simulation studies are presented validating the analytic findings.

Optimal Guidance for Accurate Lunar Soft Landing with Minimum Fuel Consumption using Model Predictive Static Programming

In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.