A novel sensing methodology using two-axis Hall-effect sensors is proposed, where the absolute positioning of a device atop any magnet matrix is possible. This methodology has the capability of micrometer-order positioning resolution as well as unrestricted translational and rotational range in planar 3-DOF (degree-of-freedom) motions, with potential capability of measuring all 6-DOF motions. This research presents the methodology and preliminary experimental results of 3-DOF planar motion measurements atop a Halbach magnet matrix using two sets of two-axis Hall-effect sensors. Analysis of the Halbach magnet matrix is presented to understand the generated magnetic field. The algorithm uses the Gaussian least squares differential correction (GLSDC) algorithm to estimate the relative position and orientation from the Hall-effect sensor measurements. A recursive discrete-time Kalman filter (DKF) is used in combination with the GLSDC to obtain optimal estimates of position and orientation, as well as additional estimates of velocity and angular velocity, which we can use to design a multivariable controller. The sensor and its algorithm is implemented to a magnetic levitation (maglev) stage positioned atop a Halbach magnet matrix. Preliminary experimental results show its position resolution capability of less than 10 µm and capable of sensing large rotations. Controllers were designed to close the control loop for the three planar degrees of freedom motion using the GLSDC outputs at a sampling frequency of 800 Hz on a Pentek 4284 digital signal processor (DSP). Calibration was done by comparing the laser interferometers’ and the GLSDC’s outputs to improve the positioning accuracy.

Spacecraft missions such as spacecraft docking and formation flying require high precision relative position and attitude data. Although Global Positioining Systems can provide this capability near the earth, deep space missions require the use of alternative technologies. One such technology is the vision-based navigation (VISNAV) sensor system developed at Texas A&M University. VISNAV comprises an electro-optical sensor combined with light sources or beacons. This patented sensor has an analog detector in the focal plane with a rise time of a few microseconds. Accuracies better than one part in 2000 of the field of view have been obtained. This research presents a new approach involving simultaneous activation of beacons with frequency division multiplexing as part of the VISNAV sensor system. In addition, it discusses the synchronous demodulation process using digital heterodyning and decimating filter banks on a low-power fixed point DSP, which improves the accuracy of the sensor measurements and the reliability of the system. This research also presents an optimal and computationally efficient six-degree-of-freedom estimation algorithm using a new measurement model based on the attitude representation of Modified Rodrigues Parameters.

Spacecraft missions such as spacecraft docking and formation flying require high precision relative position and attitude data. Although Global Positioining Systems can provide this capability near the earth, deep space missions require the use of alternative technologies. One such technology is the vision-based navigation (VISNAV) sensor system developed at Texas A&M University. VISNAV comprises an electro-optical sensor combined with light sources or beacons. This patented sensor has an analog detector in the focal plane with a rise time of a few microseconds. Accuracies better than one part in 2000 of the field of view have been obtained. This research presents a new approach involving simultaneous activation of beacons with frequency division multiplexing as part of the VISNAV sensor system. In addition, it discusses the synchronous demodulation process using digital heterodyning and decimating filter banks on a low-power fixed point DSP, which improves the accuracy of the sensor measurements and the reliability of the system. This research also presents an optimal and computationally efficient six-degree-of-freedom estimation algorithm using a new measurement model based on the attitude representation of Modified Rodrigues Parameters.