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AN3182 датащи(PDF) 14 Page - STMicroelectronics |
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AN3182 датащи(HTML) 14 Page - STMicroelectronics |
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14 / 18 page ![]() Least square method AN3182 14/18 Doc ID 17289 Rev 1 Appendix A Least square method Let's consider accelerometer calibration at the 6 stationary positions shown in Table 2. Equation 1 can be rewritten as: Equation 10 Or Equation 11 where: ● Matrix X is the 12 calibration parameters that need to be determined ● Matrix w is sensor raw data LSBs collected at 6 stationary positions ● Matrix Y is the known normalized Earth gravity vector For example, ● At Zb down position (P1 position), , and assume that at Zb down position, n1 sets of accelerometer raw data Ax, Ay and Az have been collected. Then, Equation 12 where: Matrix Y1 has the same row of [0 0 1]. Matrix w1 contains raw data in the format of LSBs. ● At Zb up position (P2 position), , and assume that at Zb up position, n2 sets of accelerometer raw data Ax, Ay and Az have been collected. Then, Equation 13 ● At Yb down position (P3 position), , and assume that at Yb down position, n3 sets of accelerometer raw data Ax, Ay and Az have been collected. Then, [] [ ] ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢ ⎣ ⎡ ⋅ = 30 20 10 33 23 13 32 22 12 31 21 11 z y x 1 z 1 y 1 x ACC ACC ACC ACC ACC ACC ACC ACC ACC ACC ACC ACC 1 A A A A A A X w Y ⋅ = [ ] [ ]1 0 0 A A A 1 z 1 y 1 x = [ ] [] 4 x 1 n 1 zP 1 yP 1 xP 1 3 x 1 n 1 1 A A A w 1 0 0 Y = = [ ] [ ]1 0 0 A A A 1 z 1 y 1 x − = [ ] [] 4 x 2 n 2 zP 2 yP 2 xP 2 3 x 2 n 2 1 A A A w 1 0 0 Y = − = [ ] [ ] 0 1 0 A A A 1 z 1 y 1 x = |
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