1 /*
2 * Copyright (C) 2016 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #include "calibration/accelerometer/accel_cal.h"
18 #include <errno.h>
19 #include <math.h>
20 #include <stdio.h>
21 #include <string.h>
22 #include "calibration/magnetometer/mag_cal.h"
23 #include "calibration/util/cal_log.h"
24
25 #define KSCALE \
26 0.101936799f // Scaling from m/s^2 to g (0.101 = 1/(9.81 m/s^2)).
27 #define KSCALE2 9.81f // Scaling from g to m/s^2.
28 #define PHI 0.707f // = 1/sqrt(2) gives a 45 degree angle for sorting data.
29 #define PHIb -0.707f
30 #define PHIZ 0.866f // smaller Z sphere cap, opening angle is 30 degrees.
31 #define PHIZb -0.866f
32 #define G_NORM_MAX \
33 1.38f // Norm during stillness should be 1 g, checking from max min values.
34 #define G_NORM_MIN 0.68f
35 #define MAX_OFF 0.1f // Will not accept offsets that are larger than 100 mg.
36 #define MIN_TEMP 20.0f // No Data is collected below 20 degree C.
37 #define MAX_TEMP 45.0f // No Data is collected above 45 degree C.
38 #define TEMP_CUT 30 // Separation point for temperature buckets 30 degree C.
39 #define EIGEN_RATIO 0.35 // EIGEN_RATIO (must be greater than 0.35).
40 #define EIGEN_MAG 0.97 // Eigen value magnitude (must be greater than 0.97).
41 #ifdef ACCEL_CAL_DBG_ENABLED
42 #define TEMP_HIST_LOW \
43 16 // Putting all Temp counts in first bucket for temp < 16 degree C.
44 #define TEMP_HIST_HIGH \
45 62 // Putting all Temp counts in last bucket for temp > 62 degree C.
46 #define HIST_COUNT 9
47 #endif
48 #ifdef IMU_TEMP_DBG_ENABLED
49 #define IMU_TEMP_DELTA_TIME_NANOS \
50 5000000000 // Printing every 5 seconds IMU temp.
51 #endif
52
53 /////////// Start Debug //////////////////////
54
55 #ifdef ACCEL_CAL_DBG_ENABLED
56 // Total bucket Counter.
accelStatsCounter(struct AccelStillDet * asd,struct AccelStatsMem * adf)57 static void accelStatsCounter(struct AccelStillDet *asd,
58 struct AccelStatsMem *adf) {
59 // Sorting the data in the different buckets
60 // x bucket ntx.
61 if (PHI < asd->mean_x) {
62 adf->ntx += 1;
63 }
64 // Negative x bucket ntxb.
65 if (PHIb > asd->mean_x) {
66 adf->ntxb += 1;
67 }
68 // Y bucket nty.
69 if (PHI < asd->mean_y) {
70 adf->nty += 1;
71 }
72 // Negative y bucket ntyb.
73 if (PHIb > asd->mean_y) {
74 adf->ntyb += 1;
75 }
76 // Z bucket ntz.
77 if (PHIZ < asd->mean_z) {
78 adf->ntz += 1;
79 }
80 // Negative z bucket ntzb.
81 if (PHIZb > asd->mean_z) {
82 adf->ntzb += 1;
83 }
84 // The leftover bucket ntle.
85 if (PHI > asd->mean_x && PHIb < asd->mean_x && PHI > asd->mean_y &&
86 PHIb < asd->mean_y && PHIZ > asd->mean_z && PHIZb < asd->mean_z) {
87 adf->ntle += 1;
88 }
89 }
90
91 // Temp histogram generation.
accelTempHisto(struct AccelStatsMem * adf,float temp)92 static void accelTempHisto(struct AccelStatsMem *adf, float temp) {
93 int index = 0;
94
95 // Take temp at every stillness detection.
96 adf->start_time_nanos = 0;
97 if (temp <= TEMP_HIST_LOW) {
98 adf->t_hist[0] += 1;
99 return;
100 }
101 if (temp >= TEMP_HIST_HIGH) {
102 adf->t_hist[TEMP_HISTOGRAM - 1] += 1;
103 return;
104 }
105 index = (int)(((temp - TEMP_HIST_LOW) / 2) + 1);
106 adf->t_hist[index] += 1;
107 }
108
109 #endif
110 ///////// End Debug ////////////////////
111
112 // Stillness detector reset.
asdReset(struct AccelStillDet * asd)113 static void asdReset(struct AccelStillDet *asd) {
114 asd->nsamples = 0;
115 asd->start_time = 0;
116 asd->acc_x = asd->acc_y = asd->acc_z = 0.0f;
117 asd->acc_xx = asd->acc_yy = asd->acc_zz = 0.0f;
118 }
119
120 // Stillness detector init.
accelStillInit(struct AccelStillDet * asd,uint32_t t0,uint32_t n_s,float th)121 static void accelStillInit(struct AccelStillDet *asd, uint32_t t0, uint32_t n_s,
122 float th) {
123 memset(asd, 0, sizeof(struct AccelStillDet));
124 asd->var_th = th;
125 asd->min_batch_window = t0;
126 asd->max_batch_window = t0 + 100000000;
127 asd->min_batch_size = n_s;
128 asd->n_still = 0;
129 }
130
131 // Good data reset.
agdReset(struct AccelGoodData * agd)132 static void agdReset(struct AccelGoodData *agd) {
133 agd->nx = agd->nxb = 0;
134 agd->ny = agd->nyb = 0;
135 agd->nz = agd->nzb = 0;
136 agd->nle = 0;
137 agd->acc_t = agd->acc_tt = 0;
138 agd->e_x = agd->e_y = agd->e_z = 0;
139 }
140
141 // Good data init.
accelGoodDataInit(struct AccelGoodData * agd,uint32_t fx,uint32_t fxb,uint32_t fy,uint32_t fyb,uint32_t fz,uint32_t fzb,uint32_t fle)142 static void accelGoodDataInit(struct AccelGoodData *agd, uint32_t fx,
143 uint32_t fxb, uint32_t fy, uint32_t fyb,
144 uint32_t fz, uint32_t fzb, uint32_t fle) {
145 memset(agd, 0, sizeof(struct AccelGoodData));
146 agd->nfx = fx;
147 agd->nfxb = fxb;
148 agd->nfy = fy;
149 agd->nfyb = fyb;
150 agd->nfz = fz;
151 agd->nfzb = fzb;
152 agd->nfle = fle;
153 agd->var_t = 0;
154 agd->mean_t = 0;
155 }
156
157 // Accel cal algo init (ready for temp buckets).
accelCalAlgoInit(struct AccelCalAlgo * acc,uint32_t fx,uint32_t fxb,uint32_t fy,uint32_t fyb,uint32_t fz,uint32_t fzb,uint32_t fle)158 static void accelCalAlgoInit(struct AccelCalAlgo *acc, uint32_t fx,
159 uint32_t fxb, uint32_t fy, uint32_t fyb,
160 uint32_t fz, uint32_t fzb, uint32_t fle) {
161 accelGoodDataInit(&acc->agd, fx, fxb, fy, fyb, fz, fzb, fle);
162 initKasa(&acc->akf);
163 }
164
165 // Accel cal init.
accelCalInit(struct AccelCal * acc,uint32_t t0,uint32_t n_s,float th,uint32_t fx,uint32_t fxb,uint32_t fy,uint32_t fyb,uint32_t fz,uint32_t fzb,uint32_t fle)166 void accelCalInit(struct AccelCal *acc, uint32_t t0, uint32_t n_s, float th,
167 uint32_t fx, uint32_t fxb, uint32_t fy, uint32_t fyb,
168 uint32_t fz, uint32_t fzb, uint32_t fle) {
169 // Init core accel data.
170 accelCalAlgoInit(&acc->ac1[0], fx, fxb, fy, fyb, fz, fzb, fle);
171 accelCalAlgoInit(&acc->ac1[1], fx, fxb, fy, fyb, fz, fzb, fle);
172
173 // Stillness Reset.
174 accelStillInit(&acc->asd, t0, n_s, th);
175
176 // Debug data init.
177 #ifdef ACCEL_CAL_DBG_ENABLED
178 memset(&acc->adf, 0, sizeof(struct AccelStatsMem));
179 #endif
180
181 acc->x_bias = acc->y_bias = acc->z_bias = 0;
182 acc->x_bias_new = acc->y_bias_new = acc->z_bias_new = 0;
183
184 #ifdef IMU_TEMP_DBG_ENABLED
185 acc->temp_time_nanos = 0;
186 #endif
187 }
188
189 // Stillness time check.
stillnessBatchComplete(struct AccelStillDet * asd,uint64_t sample_time_nanos)190 static int stillnessBatchComplete(struct AccelStillDet *asd,
191 uint64_t sample_time_nanos) {
192 int complete = 0;
193
194 // Checking if enough data is accumulated to calc Mean and Var.
195 if ((sample_time_nanos - asd->start_time > asd->min_batch_window) &&
196 (asd->nsamples > asd->min_batch_size)) {
197 if (sample_time_nanos - asd->start_time < asd->max_batch_window) {
198 complete = 1;
199 } else {
200 // Checking for too long batch window, if yes reset and start over.
201 asdReset(asd);
202 return complete;
203 }
204 } else if (sample_time_nanos - asd->start_time > asd->min_batch_window &&
205 (asd->nsamples < asd->min_batch_size)) {
206 // Not enough samples collected in max_batch_window during sample window.
207 asdReset(asd);
208 }
209 return complete;
210 }
211
212 // Releasing Memory.
accelCalDestroy(struct AccelCal * acc)213 void accelCalDestroy(struct AccelCal *acc) { (void)acc; }
214
215 // Stillness Detection.
accelStillnessDetection(struct AccelStillDet * asd,uint64_t sample_time_nanos,float x,float y,float z)216 static int accelStillnessDetection(struct AccelStillDet *asd,
217 uint64_t sample_time_nanos, float x, float y,
218 float z) {
219 float inv = 0.0f;
220 int complete = 0.0f;
221 float g_norm = 0.0f;
222
223 // Accumulate for mean and VAR.
224 asd->acc_x += x;
225 asd->acc_xx += x * x;
226 asd->acc_y += y;
227 asd->acc_yy += y * y;
228 asd->acc_z += z;
229 asd->acc_zz += z * z;
230
231 // Setting a new start time and wait until T0 is reached.
232 if (++asd->nsamples == 1) {
233 asd->start_time = sample_time_nanos;
234 }
235 if (stillnessBatchComplete(asd, sample_time_nanos)) {
236 // Getting 1/#samples and checking asd->nsamples != 0.
237 if (0 < asd->nsamples) {
238 inv = 1.0f / asd->nsamples;
239 } else {
240 // Something went wrong resetting and start over.
241 asdReset(asd);
242 return complete;
243 }
244 // Calculating the VAR = sum(x^2)/n - sum(x)^2/n^2.
245 asd->var_x = (asd->acc_xx - (asd->acc_x * asd->acc_x) * inv) * inv;
246 asd->var_y = (asd->acc_yy - (asd->acc_y * asd->acc_y) * inv) * inv;
247 asd->var_z = (asd->acc_zz - (asd->acc_z * asd->acc_z) * inv) * inv;
248 // Checking if sensor is still.
249 if (asd->var_x < asd->var_th && asd->var_y < asd->var_th &&
250 asd->var_z < asd->var_th) {
251 // Calcluating the MEAN = sum(x) / n.
252 asd->mean_x = asd->acc_x * inv;
253 asd->mean_y = asd->acc_y * inv;
254 asd->mean_z = asd->acc_z * inv;
255 // Calculating g_norm^2.
256 g_norm = asd->mean_x * asd->mean_x + asd->mean_y * asd->mean_y +
257 asd->mean_z * asd->mean_z;
258 // Magnitude check, still passsing when we have worse case offset.
259 if (g_norm < G_NORM_MAX && g_norm > G_NORM_MIN) {
260 complete = 1;
261 asd->n_still += 1;
262 }
263 }
264 asdReset(asd);
265 }
266 return complete;
267 }
268
269 // Accumulate data for KASA fit.
accelCalUpdate(struct KasaFit * akf,struct AccelStillDet * asd)270 static void accelCalUpdate(struct KasaFit *akf, struct AccelStillDet *asd) {
271 // Run accumulators.
272 float w = asd->mean_x * asd->mean_x + asd->mean_y * asd->mean_y +
273 asd->mean_z * asd->mean_z;
274
275 akf->acc_x += asd->mean_x;
276 akf->acc_y += asd->mean_y;
277 akf->acc_z += asd->mean_z;
278 akf->acc_w += w;
279
280 akf->acc_xx += asd->mean_x * asd->mean_x;
281 akf->acc_xy += asd->mean_x * asd->mean_y;
282 akf->acc_xz += asd->mean_x * asd->mean_z;
283 akf->acc_xw += asd->mean_x * w;
284
285 akf->acc_yy += asd->mean_y * asd->mean_y;
286 akf->acc_yz += asd->mean_y * asd->mean_z;
287 akf->acc_yw += asd->mean_y * w;
288
289 akf->acc_zz += asd->mean_z * asd->mean_z;
290 akf->acc_zw += asd->mean_z * w;
291 akf->nsamples += 1;
292 }
293
294 // Good data detection, sorting and accumulate the data for Kasa.
accelGoodData(struct AccelStillDet * asd,struct AccelCalAlgo * ac1,float temp)295 static int accelGoodData(struct AccelStillDet *asd, struct AccelCalAlgo *ac1,
296 float temp) {
297 int complete = 0;
298 float inv = 0.0f;
299
300 // Sorting the data in the different buckets and accum
301 // x bucket nx.
302 if (PHI < asd->mean_x && ac1->agd.nx < ac1->agd.nfx) {
303 ac1->agd.nx += 1;
304 ac1->agd.acc_t += temp;
305 ac1->agd.acc_tt += temp * temp;
306 accelCalUpdate(&ac1->akf, asd);
307 }
308 // Negative x bucket nxb.
309 if (PHIb > asd->mean_x && ac1->agd.nxb < ac1->agd.nfxb) {
310 ac1->agd.nxb += 1;
311 ac1->agd.acc_t += temp;
312 ac1->agd.acc_tt += temp * temp;
313 accelCalUpdate(&ac1->akf, asd);
314 }
315 // Y bucket ny.
316 if (PHI < asd->mean_y && ac1->agd.ny < ac1->agd.nfy) {
317 ac1->agd.ny += 1;
318 ac1->agd.acc_t += temp;
319 ac1->agd.acc_tt += temp * temp;
320 accelCalUpdate(&ac1->akf, asd);
321 }
322 // Negative y bucket nyb.
323 if (PHIb > asd->mean_y && ac1->agd.nyb < ac1->agd.nfyb) {
324 ac1->agd.nyb += 1;
325 ac1->agd.acc_t += temp;
326 ac1->agd.acc_tt += temp * temp;
327 accelCalUpdate(&ac1->akf, asd);
328 }
329 // Z bucket nz.
330 if (PHIZ < asd->mean_z && ac1->agd.nz < ac1->agd.nfz) {
331 ac1->agd.nz += 1;
332 ac1->agd.acc_t += temp;
333 ac1->agd.acc_tt += temp * temp;
334 accelCalUpdate(&ac1->akf, asd);
335 }
336 // Negative z bucket nzb.
337 if (PHIZb > asd->mean_z && ac1->agd.nzb < ac1->agd.nfzb) {
338 ac1->agd.nzb += 1;
339 ac1->agd.acc_t += temp;
340 ac1->agd.acc_tt += temp * temp;
341 accelCalUpdate(&ac1->akf, asd);
342 }
343 // The leftover bucket nle.
344 if (PHI > asd->mean_x && PHIb < asd->mean_x && PHI > asd->mean_y &&
345 PHIb < asd->mean_y && PHIZ > asd->mean_z && PHIZb < asd->mean_z &&
346 ac1->agd.nle < ac1->agd.nfle) {
347 ac1->agd.nle += 1;
348 ac1->agd.acc_t += temp;
349 ac1->agd.acc_tt += temp * temp;
350 accelCalUpdate(&ac1->akf, asd);
351 }
352 // Checking if all buckets are full.
353 if (ac1->agd.nx == ac1->agd.nfx && ac1->agd.nxb == ac1->agd.nfxb &&
354 ac1->agd.ny == ac1->agd.nfy && ac1->agd.nyb == ac1->agd.nfyb &&
355 ac1->agd.nz == ac1->agd.nfz && ac1->agd.nzb == ac1->agd.nfzb) {
356 // Check if akf->nsamples is zero.
357 if (ac1->akf.nsamples == 0) {
358 agdReset(&ac1->agd);
359 magKasaReset(&ac1->akf);
360 complete = 0;
361 return complete;
362 } else {
363 // Normalize the data to the sample numbers.
364 inv = 1.0f / ac1->akf.nsamples;
365 }
366
367 ac1->akf.acc_x *= inv;
368 ac1->akf.acc_y *= inv;
369 ac1->akf.acc_z *= inv;
370 ac1->akf.acc_w *= inv;
371
372 ac1->akf.acc_xx *= inv;
373 ac1->akf.acc_xy *= inv;
374 ac1->akf.acc_xz *= inv;
375 ac1->akf.acc_xw *= inv;
376
377 ac1->akf.acc_yy *= inv;
378 ac1->akf.acc_yz *= inv;
379 ac1->akf.acc_yw *= inv;
380
381 ac1->akf.acc_zz *= inv;
382 ac1->akf.acc_zw *= inv;
383
384 // Calculate the temp VAR and MEA.N
385 ac1->agd.var_t =
386 (ac1->agd.acc_tt - (ac1->agd.acc_t * ac1->agd.acc_t) * inv) * inv;
387 ac1->agd.mean_t = ac1->agd.acc_t * inv;
388 complete = 1;
389 }
390
391 // If any of the buckets has a bigger number as specified, reset and start
392 // over.
393 if (ac1->agd.nx > ac1->agd.nfx || ac1->agd.nxb > ac1->agd.nfxb ||
394 ac1->agd.ny > ac1->agd.nfy || ac1->agd.nyb > ac1->agd.nfyb ||
395 ac1->agd.nz > ac1->agd.nfz || ac1->agd.nzb > ac1->agd.nfzb) {
396 agdReset(&ac1->agd);
397 magKasaReset(&ac1->akf);
398 complete = 0;
399 return complete;
400 }
401 return complete;
402 }
403
404 // Eigen value magnitude and ratio test.
accEigenTest(struct KasaFit * akf,struct AccelGoodData * agd)405 static int accEigenTest(struct KasaFit *akf, struct AccelGoodData *agd) {
406 // covariance matrix.
407 struct Mat33 S;
408 S.elem[0][0] = akf->acc_xx - akf->acc_x * akf->acc_x;
409 S.elem[0][1] = S.elem[1][0] = akf->acc_xy - akf->acc_x * akf->acc_y;
410 S.elem[0][2] = S.elem[2][0] = akf->acc_xz - akf->acc_x * akf->acc_z;
411 S.elem[1][1] = akf->acc_yy - akf->acc_y * akf->acc_y;
412 S.elem[1][2] = S.elem[2][1] = akf->acc_yz - akf->acc_y * akf->acc_z;
413 S.elem[2][2] = akf->acc_zz - akf->acc_z * akf->acc_z;
414
415 struct Vec3 eigenvals;
416 struct Mat33 eigenvecs;
417 mat33GetEigenbasis(&S, &eigenvals, &eigenvecs);
418
419 float evmax = (eigenvals.x > eigenvals.y) ? eigenvals.x : eigenvals.y;
420 evmax = (eigenvals.z > evmax) ? eigenvals.z : evmax;
421
422 float evmin = (eigenvals.x < eigenvals.y) ? eigenvals.x : eigenvals.y;
423 evmin = (eigenvals.z < evmin) ? eigenvals.z : evmin;
424
425 float evmag = sqrtf(eigenvals.x + eigenvals.y + eigenvals.z);
426 // Passing when evmin/evmax> EIGEN_RATIO.
427 int eigen_pass = (evmin > evmax * EIGEN_RATIO) && (evmag > EIGEN_MAG);
428
429 agd->e_x = eigenvals.x;
430 agd->e_y = eigenvals.y;
431 agd->e_z = eigenvals.z;
432
433 return eigen_pass;
434 }
435
436 // Updating the new bias and save to pointers. Return true if the bias changed.
accelCalUpdateBias(struct AccelCal * acc,float * x,float * y,float * z)437 bool accelCalUpdateBias(struct AccelCal *acc, float *x, float *y, float *z) {
438 *x = acc->x_bias_new;
439 *y = acc->y_bias_new;
440 *z = acc->z_bias_new;
441
442 // Check to see if the bias changed since last call to accelCalUpdateBias.
443 // Compiler does not allow us to use "==" and "!=" when comparing floats, so
444 // just use "<" and ">".
445 if ((acc->x_bias < acc->x_bias_new) || (acc->x_bias > acc->x_bias_new) ||
446 (acc->y_bias < acc->y_bias_new) || (acc->y_bias > acc->y_bias_new) ||
447 (acc->z_bias < acc->z_bias_new) || (acc->z_bias > acc->z_bias_new)) {
448 acc->x_bias = acc->x_bias_new;
449 acc->y_bias = acc->y_bias_new;
450 acc->z_bias = acc->z_bias_new;
451 return true;
452 }
453
454 return false;
455 }
456
457 // Set the (initial) bias.
accelCalBiasSet(struct AccelCal * acc,float x,float y,float z)458 void accelCalBiasSet(struct AccelCal *acc, float x, float y, float z) {
459 acc->x_bias = acc->x_bias_new = x;
460 acc->y_bias = acc->y_bias_new = y;
461 acc->z_bias = acc->z_bias_new = z;
462 }
463
464 // Removing the bias.
accelCalBiasRemove(struct AccelCal * acc,float * x,float * y,float * z)465 void accelCalBiasRemove(struct AccelCal *acc, float *x, float *y, float *z) {
466 *x = *x - acc->x_bias;
467 *y = *y - acc->y_bias;
468 *z = *z - acc->z_bias;
469 }
470
471 // Accel Cal Runner.
accelCalRun(struct AccelCal * acc,uint64_t sample_time_nanos,float x,float y,float z,float temp)472 void accelCalRun(struct AccelCal *acc, uint64_t sample_time_nanos, float x,
473 float y, float z, float temp) {
474 // Scaling to 1g, better for the algorithm.
475 x *= KSCALE;
476 y *= KSCALE;
477 z *= KSCALE;
478
479 // DBG: IMU temp messages every 5s.
480 #ifdef IMU_TEMP_DBG_ENABLED
481 if ((sample_time_nanos - acc->temp_time_nanos) > IMU_TEMP_DELTA_TIME_NANOS) {
482 CAL_DEBUG_LOG("IMU Temp Data: ",
483 ", %s%d.%02d, %llu, %s%d.%05d, %s%d.%05d, %s%d.%05d \n",
484 CAL_ENCODE_FLOAT(temp, 2),
485 (unsigned long long int)sample_time_nanos,
486 CAL_ENCODE_FLOAT(acc->x_bias_new,5),
487 CAL_ENCODE_FLOAT(acc->y_bias_new,5),
488 CAL_ENCODE_FLOAT(acc->z_bias_new,5));
489 acc->temp_time_nanos = sample_time_nanos;
490 }
491 #endif
492
493 int temp_gate = 0;
494
495 // Temp GATE.
496 if (temp < MAX_TEMP && temp > MIN_TEMP) {
497 // Checking if accel is still.
498 if (accelStillnessDetection(&acc->asd, sample_time_nanos, x, y, z)) {
499 #ifdef ACCEL_CAL_DBG_ENABLED
500 // Creating temp hist data.
501 accelTempHisto(&acc->adf, temp);
502 #endif
503
504 // Two temp buckets.
505 if (temp < TEMP_CUT) {
506 temp_gate = 0;
507 } else {
508 temp_gate = 1;
509 }
510 #ifdef ACCEL_CAL_DBG_ENABLED
511 accelStatsCounter(&acc->asd, &acc->adf);
512 #endif
513 // If still -> pass the averaged accel data (mean) to the
514 // sorting, counting and accum function.
515 if (accelGoodData(&acc->asd, &acc->ac1[temp_gate], temp)) {
516 // Running the Kasa fit.
517 struct Vec3 bias;
518 float radius;
519
520 // Grabbing the fit from the MAG cal.
521 magKasaFit(&acc->ac1[temp_gate].akf, &bias, &radius);
522
523 // If offset is too large don't take.
524 if (fabsf(bias.x) < MAX_OFF && fabsf(bias.y) < MAX_OFF &&
525 fabsf(bias.z) < MAX_OFF) {
526 // Eigen Ratio Test.
527 if (accEigenTest(&acc->ac1[temp_gate].akf,
528 &acc->ac1[temp_gate].agd)) {
529 // Storing the new offsets.
530 acc->x_bias_new = bias.x * KSCALE2;
531 acc->y_bias_new = bias.y * KSCALE2;
532 acc->z_bias_new = bias.z * KSCALE2;
533 }
534 #ifdef ACCEL_CAL_DBG_ENABLED
535 //// Debug ///////
536 acc->adf.noff += 1;
537 // Resetting the counter for the offset history.
538 if (acc->adf.n_o > HIST_COUNT) {
539 acc->adf.n_o = 0;
540 }
541
542 // Storing the Debug data.
543 acc->adf.x_o[acc->adf.n_o] = bias.x;
544 acc->adf.y_o[acc->adf.n_o] = bias.y;
545 acc->adf.z_o[acc->adf.n_o] = bias.z;
546 acc->adf.e_x[acc->adf.n_o] = acc->ac1[temp_gate].agd.e_x;
547 acc->adf.e_y[acc->adf.n_o] = acc->ac1[temp_gate].agd.e_y;
548 acc->adf.e_z[acc->adf.n_o] = acc->ac1[temp_gate].agd.e_z;
549 acc->adf.var_t[acc->adf.n_o] = acc->ac1[temp_gate].agd.var_t;
550 acc->adf.mean_t[acc->adf.n_o] = acc->ac1[temp_gate].agd.mean_t;
551 acc->adf.cal_time[acc->adf.n_o] = sample_time_nanos;
552 acc->adf.rad[acc->adf.n_o] = radius;
553 acc->adf.n_o += 1;
554 #endif
555 } else {
556 #ifdef ACCEL_CAL_DBG_ENABLED
557 acc->adf.noff_max += 1;
558 #endif
559 }
560 ///////////////
561
562 // Resetting the structs for a new accel cal run.
563 agdReset(&acc->ac1[temp_gate].agd);
564 magKasaReset(&acc->ac1[temp_gate].akf);
565 }
566 }
567 }
568 }
569
570 #ifdef ACCEL_CAL_DBG_ENABLED
571 // Debug Print Output
accelCalDebPrint(struct AccelCal * acc,float temp)572 void accelCalDebPrint(struct AccelCal *acc, float temp) {
573 static int32_t kk = 0;
574 if (++kk == 1000) {
575 // X offset history last 10 values.
576 CAL_DEBUG_LOG(
577 "[BMI160]",
578 "{MK_ACCEL,11,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
579 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(x_off history)\n",
580 CAL_ENCODE_FLOAT(acc->adf.x_o[0], 6),
581 CAL_ENCODE_FLOAT(acc->adf.x_o[1], 6),
582 CAL_ENCODE_FLOAT(acc->adf.x_o[2], 6),
583 CAL_ENCODE_FLOAT(acc->adf.x_o[3], 6),
584 CAL_ENCODE_FLOAT(acc->adf.x_o[4], 6),
585 CAL_ENCODE_FLOAT(acc->adf.x_o[5], 6),
586 CAL_ENCODE_FLOAT(acc->adf.x_o[6], 6),
587 CAL_ENCODE_FLOAT(acc->adf.x_o[7], 6),
588 CAL_ENCODE_FLOAT(acc->adf.x_o[8], 6),
589 CAL_ENCODE_FLOAT(acc->adf.x_o[9], 6));
590
591 // Y offset history last 10 values.
592 CAL_DEBUG_LOG(
593 "[BMI160]",
594 "{MK_ACCEL,12,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
595 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(y_off history)\n",
596 CAL_ENCODE_FLOAT(acc->adf.y_o[0], 6),
597 CAL_ENCODE_FLOAT(acc->adf.y_o[1], 6),
598 CAL_ENCODE_FLOAT(acc->adf.y_o[2], 6),
599 CAL_ENCODE_FLOAT(acc->adf.y_o[3], 6),
600 CAL_ENCODE_FLOAT(acc->adf.y_o[4], 6),
601 CAL_ENCODE_FLOAT(acc->adf.y_o[5], 6),
602 CAL_ENCODE_FLOAT(acc->adf.y_o[6], 6),
603 CAL_ENCODE_FLOAT(acc->adf.y_o[7], 6),
604 CAL_ENCODE_FLOAT(acc->adf.y_o[8], 6),
605 CAL_ENCODE_FLOAT(acc->adf.y_o[9], 6));
606
607 // Z offset history last 10 values.
608 CAL_DEBUG_LOG(
609 "[BMI160]",
610 "{MK_ACCEL,13,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
611 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(z_off history)\n",
612 CAL_ENCODE_FLOAT(acc->adf.z_o[0], 6),
613 CAL_ENCODE_FLOAT(acc->adf.z_o[1], 6),
614 CAL_ENCODE_FLOAT(acc->adf.z_o[2], 6),
615 CAL_ENCODE_FLOAT(acc->adf.z_o[3], 6),
616 CAL_ENCODE_FLOAT(acc->adf.z_o[4], 6),
617 CAL_ENCODE_FLOAT(acc->adf.z_o[5], 6),
618 CAL_ENCODE_FLOAT(acc->adf.z_o[6], 6),
619 CAL_ENCODE_FLOAT(acc->adf.z_o[7], 6),
620 CAL_ENCODE_FLOAT(acc->adf.z_o[8], 6),
621 CAL_ENCODE_FLOAT(acc->adf.z_o[9], 6));
622
623 // Temp history variation VAR of offset.
624 CAL_DEBUG_LOG(
625 "[BMI160]",
626 "{MK_ACCEL,14,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
627 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(VAR temp history)\n",
628 CAL_ENCODE_FLOAT(acc->adf.var_t[0], 6),
629 CAL_ENCODE_FLOAT(acc->adf.var_t[1], 6),
630 CAL_ENCODE_FLOAT(acc->adf.var_t[2], 6),
631 CAL_ENCODE_FLOAT(acc->adf.var_t[3], 6),
632 CAL_ENCODE_FLOAT(acc->adf.var_t[4], 6),
633 CAL_ENCODE_FLOAT(acc->adf.var_t[5], 6),
634 CAL_ENCODE_FLOAT(acc->adf.var_t[6], 6),
635 CAL_ENCODE_FLOAT(acc->adf.var_t[7], 6),
636 CAL_ENCODE_FLOAT(acc->adf.var_t[8], 6),
637 CAL_ENCODE_FLOAT(acc->adf.var_t[9], 6));
638
639 // Temp mean history of offset.
640 CAL_DEBUG_LOG(
641 "[BMI160]",
642 "{MK_ACCEL,15,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
643 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(MEAN Temp history)\n",
644 CAL_ENCODE_FLOAT(acc->adf.mean_t[0], 6),
645 CAL_ENCODE_FLOAT(acc->adf.mean_t[1], 6),
646 CAL_ENCODE_FLOAT(acc->adf.mean_t[2], 6),
647 CAL_ENCODE_FLOAT(acc->adf.mean_t[3], 6),
648 CAL_ENCODE_FLOAT(acc->adf.mean_t[4], 6),
649 CAL_ENCODE_FLOAT(acc->adf.mean_t[5], 6),
650 CAL_ENCODE_FLOAT(acc->adf.mean_t[6], 6),
651 CAL_ENCODE_FLOAT(acc->adf.mean_t[7], 6),
652 CAL_ENCODE_FLOAT(acc->adf.mean_t[8], 6),
653 CAL_ENCODE_FLOAT(acc->adf.mean_t[9], 6));
654
655 // KASA radius history.
656 CAL_DEBUG_LOG(
657 "[BMI160]",
658 "{MK_ACCEL,16,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
659 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(radius)\n",
660 CAL_ENCODE_FLOAT(acc->adf.rad[0], 6),
661 CAL_ENCODE_FLOAT(acc->adf.rad[1], 6),
662 CAL_ENCODE_FLOAT(acc->adf.rad[2], 6),
663 CAL_ENCODE_FLOAT(acc->adf.rad[3], 6),
664 CAL_ENCODE_FLOAT(acc->adf.rad[4], 6),
665 CAL_ENCODE_FLOAT(acc->adf.rad[5], 6),
666 CAL_ENCODE_FLOAT(acc->adf.rad[6], 6),
667 CAL_ENCODE_FLOAT(acc->adf.rad[7], 6),
668 CAL_ENCODE_FLOAT(acc->adf.rad[8], 6),
669 CAL_ENCODE_FLOAT(acc->adf.rad[9], 6));
670 kk = 0;
671 }
672
673 if (kk == 750) {
674 // Eigen Vector X.
675 CAL_DEBUG_LOG(
676 "[BMI160]",
677 "{MK_ACCEL, "
678 "7,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
679 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(eigen x)\n",
680 CAL_ENCODE_FLOAT(acc->adf.e_x[0], 6),
681 CAL_ENCODE_FLOAT(acc->adf.e_x[1], 6),
682 CAL_ENCODE_FLOAT(acc->adf.e_x[2], 6),
683 CAL_ENCODE_FLOAT(acc->adf.e_x[3], 6),
684 CAL_ENCODE_FLOAT(acc->adf.e_x[4], 6),
685 CAL_ENCODE_FLOAT(acc->adf.e_x[5], 6),
686 CAL_ENCODE_FLOAT(acc->adf.e_x[6], 6),
687 CAL_ENCODE_FLOAT(acc->adf.e_x[7], 6),
688 CAL_ENCODE_FLOAT(acc->adf.e_x[8], 6),
689 CAL_ENCODE_FLOAT(acc->adf.e_x[9], 6));
690 // Y.
691 CAL_DEBUG_LOG(
692 "[BMI160]",
693 "{MK_ACCEL, "
694 "8,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
695 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(eigen y)\n",
696 CAL_ENCODE_FLOAT(acc->adf.e_y[0], 6),
697 CAL_ENCODE_FLOAT(acc->adf.e_y[1], 6),
698 CAL_ENCODE_FLOAT(acc->adf.e_y[2], 6),
699 CAL_ENCODE_FLOAT(acc->adf.e_y[3], 6),
700 CAL_ENCODE_FLOAT(acc->adf.e_y[4], 6),
701 CAL_ENCODE_FLOAT(acc->adf.e_y[5], 6),
702 CAL_ENCODE_FLOAT(acc->adf.e_y[6], 6),
703 CAL_ENCODE_FLOAT(acc->adf.e_y[7], 6),
704 CAL_ENCODE_FLOAT(acc->adf.e_y[8], 6),
705 CAL_ENCODE_FLOAT(acc->adf.e_y[9], 6));
706 // Z.
707 CAL_DEBUG_LOG(
708 "[BMI160]",
709 "{MK_ACCEL, "
710 "9,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,%s%d.%"
711 "06d,%s%d.%06d,%s%d.%06d,%s%d.%06d,}(eigen z)\n",
712 CAL_ENCODE_FLOAT(acc->adf.e_z[0], 6),
713 CAL_ENCODE_FLOAT(acc->adf.e_z[1], 6),
714 CAL_ENCODE_FLOAT(acc->adf.e_z[2], 6),
715 CAL_ENCODE_FLOAT(acc->adf.e_z[3], 6),
716 CAL_ENCODE_FLOAT(acc->adf.e_z[4], 6),
717 CAL_ENCODE_FLOAT(acc->adf.e_z[5], 6),
718 CAL_ENCODE_FLOAT(acc->adf.e_z[6], 6),
719 CAL_ENCODE_FLOAT(acc->adf.e_z[7], 6),
720 CAL_ENCODE_FLOAT(acc->adf.e_z[8], 6),
721 CAL_ENCODE_FLOAT(acc->adf.e_z[9], 6));
722 // Accel Time in ns.
723 CAL_DEBUG_LOG(
724 "[BMI160]",
725 "{MK_ACCEL,10,%llu,%llu,%llu,%llu,%llu,%llu,%llu,%llu,%llu,%llu,}("
726 "timestamp ns)\n",
727 acc->adf.cal_time[0], acc->adf.cal_time[1], acc->adf.cal_time[2],
728 acc->adf.cal_time[3], acc->adf.cal_time[4], acc->adf.cal_time[5],
729 acc->adf.cal_time[6], acc->adf.cal_time[7], acc->adf.cal_time[8],
730 acc->adf.cal_time[9]);
731 }
732
733 if (kk == 500) {
734 // Total bucket count.
735 CAL_DEBUG_LOG(
736 "[BMI160]",
737 "{MK_ACCEL, 0,%2d, %2d, %2d, %2d, %2d, %2d, %2d,}(Total Bucket #)\n",
738 (unsigned)acc->adf.ntx, (unsigned)acc->adf.ntxb, (unsigned)acc->adf.nty,
739 (unsigned)acc->adf.ntyb, (unsigned)acc->adf.ntz,
740 (unsigned)acc->adf.ntzb, (unsigned)acc->adf.ntle);
741 // Live bucket count lower.
742 CAL_DEBUG_LOG(
743 "[BMI160]",
744 "{MK_ACCEL, 1,%2d, %2d, %2d, %2d, %2d, %2d, %2d, %3d,}(Bucket # "
745 "lower)\n",
746 (unsigned)acc->ac1[0].agd.nx, (unsigned)acc->ac1[0].agd.nxb,
747 (unsigned)acc->ac1[0].agd.ny, (unsigned)acc->ac1[0].agd.nyb,
748 (unsigned)acc->ac1[0].agd.nz, (unsigned)acc->ac1[0].agd.nzb,
749 (unsigned)acc->ac1[0].agd.nle, (unsigned)acc->ac1[0].akf.nsamples);
750 // Live bucket count hogher.
751 CAL_DEBUG_LOG(
752 "[BMI160]",
753 "{MK_ACCEL, 2,%2d, %2d, %2d, %2d, %2d, %2d, %2d, %3d,}(Bucket # "
754 "higher)\n",
755 (unsigned)acc->ac1[1].agd.nx, (unsigned)acc->ac1[1].agd.nxb,
756 (unsigned)acc->ac1[1].agd.ny, (unsigned)acc->ac1[1].agd.nyb,
757 (unsigned)acc->ac1[1].agd.nz, (unsigned)acc->ac1[1].agd.nzb,
758 (unsigned)acc->ac1[1].agd.nle, (unsigned)acc->ac1[1].akf.nsamples);
759 // Offset used.
760 CAL_DEBUG_LOG(
761 "[BMI160]",
762 "{MK_ACCEL, 3,%s%d.%06d, %s%d.%06d, %s%d.%06d, %2d,}(updated offset "
763 "x,y,z, total # of offsets)\n",
764 CAL_ENCODE_FLOAT(acc->x_bias, 6), CAL_ENCODE_FLOAT(acc->y_bias, 6),
765 CAL_ENCODE_FLOAT(acc->z_bias, 6), (unsigned)acc->adf.noff);
766 // Offset New.
767 CAL_DEBUG_LOG(
768 "[BMI160]",
769 "{MK_ACCEL, 4,%s%d.%06d, %s%d.%06d, %s%d.%06d, %s%d.%06d,}(New offset "
770 "x,y,z, live temp)\n",
771 CAL_ENCODE_FLOAT(acc->x_bias_new, 6),
772 CAL_ENCODE_FLOAT(acc->y_bias_new, 6),
773 CAL_ENCODE_FLOAT(acc->z_bias_new, 6), CAL_ENCODE_FLOAT(temp, 6));
774 // Temp Histogram.
775 CAL_DEBUG_LOG(
776 "[BMI160]",
777 "{MK_ACCEL, 5,%7d, %7d, %7d, %7d, %7d, %7d, %7d, %7d, %7d, %7d, %7d, "
778 "%7d, %7d,}(temp histo)\n",
779 (unsigned)acc->adf.t_hist[0], (unsigned)acc->adf.t_hist[1],
780 (unsigned)acc->adf.t_hist[2], (unsigned)acc->adf.t_hist[3],
781 (unsigned)acc->adf.t_hist[4], (unsigned)acc->adf.t_hist[5],
782 (unsigned)acc->adf.t_hist[6], (unsigned)acc->adf.t_hist[7],
783 (unsigned)acc->adf.t_hist[8], (unsigned)acc->adf.t_hist[9],
784 (unsigned)acc->adf.t_hist[10], (unsigned)acc->adf.t_hist[11],
785 (unsigned)acc->adf.t_hist[12]);
786 CAL_DEBUG_LOG(
787 "[BMI160]",
788 "M{K_ACCEL, 6,%7d, %7d, %7d,%7d, %7d, %7d, %7d, %7d, %7d, %7d, %7d, "
789 "%7d,}(temp histo)\n",
790 (unsigned)acc->adf.t_hist[13], (unsigned)acc->adf.t_hist[14],
791 (unsigned)acc->adf.t_hist[15], (unsigned)acc->adf.t_hist[16],
792 (unsigned)acc->adf.t_hist[17], (unsigned)acc->adf.t_hist[18],
793 (unsigned)acc->adf.t_hist[19], (unsigned)acc->adf.t_hist[20],
794 (unsigned)acc->adf.t_hist[21], (unsigned)acc->adf.t_hist[22],
795 (unsigned)acc->adf.t_hist[23], (unsigned)acc->adf.t_hist[24]);
796 }
797 }
798 #endif
799