Roll angle measurement is an essential technology in the trajectory correction projectiles. In this paper, an algorithm to detect the roll angle and rotational speed of a spinning vehicle is studied by using a GPS (Global Positioning System) receiver with a single side-mounted antenna. A Frequency-Locked Loop (FLL) assisted Phase-Locked Loop (PLL) is designed to obtain the attitude information from GPS signals, and the optimal parameters of this system are discussed when different rotational speeds are considered. The error estimation of this method and signal-to-noise ratio analysis of GPS signals are also studied. Finally, experiments on the rotary table were carried out to verify the proposed method. The experimental results showed that the proposed algorithm can detect the roll angle in a precision of within 5 degrees.

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The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods.

As roll angle measurement is essential for two-dimensional course correction fuze (2-D CCF) technology, a real-time estimation of roll angle of spinning projectile by single-axis magnetometer is studied. Based on the measurement model, a second-order frequency-locked loop (FLL)-assisted third-order phase-locked loop (PLL) is designed to obtain rolling information from magnetic signals, which is less dependent on the amplitude and able to reduce effect from geomagnetic blind area. Method of parameters optimization of tracking loop is discussed in the circumstance of different speed and it is verified by six degrees of freedom (six degrees of freedom (DoF)) trajectory. Also, the measurement error is analyzed to improve the accuracy of designed system. At last, experiments on rotary table are carried out to validate the proposed method indicating the designed system is able to track both phase and speed accurately and stably. The standard deviation (SD) of phase error is no more than 3°.

The strap-down missile-borne image guidance system can be easily affected by the unwanted jitters of the motion of the camera, and the subsequent recognition and tracking functions are also influenced, thus severely affecting the navigation accuracy of the image guidance system. So, a real-time image stabilization technology is needed to help improve the image quality of the image guidance system. To satisfy the real-time and accuracy requirements of image stabilization in the strap-down missile-borne image guidance system, an image stabilization method based on optical flow and image matching with binary feature descriptors is proposed. The global motion of consecutive frames is estimated by the pyramid Lucas-Kanade (LK) optical flow algorithm, and the interval frames image matching based on fast retina keypoint (FREAK) algorithm is used to reduce the cumulative trajectory error. A Kalman filter is designed to smooth the trajectory, which is conducive to fitting to the main motion of the guidance system. Simulations have been carried out, and the results show that the proposed algorithm improves the accuracy and real-time performance simultaneously compared to the state-of-art algorithms.