Two-sample rotation vector pose algorithm ip core

Abstract

The present invention discloses a two-sample rotation vector attitude algorithm IP (Intellectual property) core. The two-sample rotation vector attitude algorithm IP core comprises a 422 interface module, an angular increment module, an equivalent rotation vector module, a quaternion transformation module, a quaternion update module, and an attitude angle calculation module. The 422 interface module comprises a frequency division module, a 422 reception module, a frame check module, an FIFO (first in, first out) storage and transmission module, an attitude angle output module, an operation result decomposition module, and a 422 output module; the frequency division module is separately connected to the 422 reception module, the operation result decomposition module, and the 422 output module; the 422 reception module gets access to the angular increment module by means of the frame check module, and the FIFO storage and transmission module; the angular increment is sequentially connected to the equivalent rotation vector module, the quaternion transformation module and the quaternion update module, and the quaternion update module separately gets access to the attitude angle calculation module and the angular increment module; and the attitude angle module gets access to the 422 output module by means of the attitude angle output module and the operation result decomposition module sequentially. The two-sample rotation vector attitude algorithm IP core disclosed by the present invention is short in running period, high in precision, and feasible in implementation of a high-speed attitude measurement component.

Description

technical field [0001] The invention belongs to the technical field of attitude measurement components, in particular to a two-sample rotation vector attitude algorithm IP core. Background technique [0002] When developing the prototype of the attitude measurement component, the attitude calculation algorithm adopted usually takes into account the error generated during the conical motion. For the SINS attitude update algorithm, the conical motion is the worst environmental condition, which will induce serious drift of the mathematical platform, so the conical motion is often used as the environmental condition in the rotation vector optimization algorithm. If we can ensure the minimum algorithm drift under the environmental conditions of cone motion, we must ensure the minimum algorithm drift under other environmental conditions. There are many factors that cause coning errors. Cone errors caused by gyro bandwidth, quantization errors, and installation errors can be overc...

AI Technical Summary

Problems solved by technology

This speed cannot meet the design of attitude measurement components with higher speed requirements

[0003] At present, the running cycle of the two-sample rotation vector attitude algorithm in the general-purpose MCU or DSP is too long, so that the calculation time cannot be further reduced, and high-speed and high-precision cannot be achieved.

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