Systems, devices, and methods for an aircraft autopilot guidance control system for guiding an aircraft having a body, the system comprising: a processor configured to determine if a yaw angle difference and a pitch angle difference meet corresponding angle thresholds; a skid-to-turn module configured to generate a skid-to-turn signal if the corresponding angle thresholds are met; a bank-to-turn module configured to generate a bank-to-turn signal having a lower bandwidth than the generated skid-to-turn signal; a rudder integrator module configured to add a rudder integrator feedback signal to the bank-to-turn signal, where the rudder integrator feedback signal is proportional to a rudder integrator; and a filter module configured to filter the generated bank-to-turn signal, wherein the filter module comprises a low-pass filter configured by a set of gains to pass the bank-to-turn signal if a side force on the body meets a side force threshold.

A target tracking apparatus includes a housing that defines an exterior surface and comprises an interior cavity, a distal opening, and an intermediate opening. The target tracking apparatus also includes a distal-end window attached to the housing over the distal opening and defining a distal end of the target tracking apparatus. The target tracking apparatus further includes an intermediate window attached to the housing over the intermediate opening. The target tracking apparatus additionally includes a first camera within the interior cavity, configured to capture images through the distal-end window, and fixed, relative to the housing, such that the first camera does not move relative to the housing. The target tracking apparatus also includes a second camera within the interior cavity, configured to capture images through the intermediate window, and fixed, relative to the housing, such that the second camera does not move relative to the housing.

The present disclosure provides methods for controlling a guided missile to account for environmental uncertainties and maintain optimal mission performance and minimize error in hitting a defined target anywhere on Earth. First, sensors collect data about the missile's environment, passing the information to storage in the missile's database and processor. Second, the missile's processor manipulates the database with a deep reinforcement learning algorithm producing instructions. Third, the instructions command the missile's control system for optimal control, target engagement, and impact by manipulating the missile's thrust vectors for guidance. In short, the disclosure provides methods for autonomous missile control which command the missile from launch to target with certainty regardless of weather conditions, environment dynamics, or defensive missile interference.