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/*
* Copyright (C) 2016 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "calibration/gyroscope/gyro_stillness_detect.h"
#include <string.h>
/////// FORWARD DECLARATIONS /////////////////////////////////////////
// Enforces the limits of an input value [0,1].
static float gyroStillDetLimit(float value);
/////// FUNCTION DEFINITIONS /////////////////////////////////////////
// Initialize the GyroStillDet structure.
void gyroStillDetInit(struct GyroStillDet* gyro_still_det, float var_threshold,
float confidence_delta) {
// Clear all data structure variables to 0.
memset(gyro_still_det, 0, sizeof(struct GyroStillDet));
// Set the delta about the variance threshold for calculation
// of the stillness confidence score.
if (confidence_delta < var_threshold) {
gyro_still_det->confidence_delta = confidence_delta;
} else {
gyro_still_det->confidence_delta = var_threshold;
}
// Set the variance threshold parameter for the stillness
// confidence score.
gyro_still_det->var_threshold = var_threshold;
// Signal to start capture of next stillness data window.
gyro_still_det->start_new_window = true;
}
// Update the stillness detector with a new sample.
void gyroStillDetUpdate(struct GyroStillDet* gyro_still_det,
uint64_t stillness_win_endtime, uint64_t sample_time,
float x, float y, float z) {
// Using the method of the assumed mean to preserve some numerical
// stability while avoiding per-sample divisions that the more
// numerically stable Welford method would afford.
// Reference for the numerical method used below to compute the
// online mean and variance statistics:
// 1). en.wikipedia.org/wiki/assumed_mean
float delta = 0;
// If the window end time is not valid then wait till it is.
if (stillness_win_endtime <= 0) {
return;
}
// Increment the number of samples.
gyro_still_det->num_acc_samples++;
// Online computation of mean for the running stillness period.
gyro_still_det->mean_x += x;
gyro_still_det->mean_y += y;
gyro_still_det->mean_z += z;
// Is this the first sample of a new window?
if (gyro_still_det->start_new_window) {
// Record the window start time.
gyro_still_det->window_start_time = sample_time;
gyro_still_det->start_new_window = false;
// Update assumed mean values.
gyro_still_det->assumed_mean_x = x;
gyro_still_det->assumed_mean_y = y;
gyro_still_det->assumed_mean_z = z;
// Reset current window mean and variance.
gyro_still_det->num_acc_win_samples = 0;
gyro_still_det->win_mean_x = 0;
gyro_still_det->win_mean_y = 0;
gyro_still_det->win_mean_z = 0;
gyro_still_det->acc_var_x = 0;
gyro_still_det->acc_var_y = 0;
gyro_still_det->acc_var_z = 0;
} else {
// Check to see if we have enough samples to compute a stillness
// confidence score.
gyro_still_det->stillness_window_ready =
(sample_time >= stillness_win_endtime) &&
(gyro_still_det->num_acc_samples > 1);
}
// Record the most recent sample time stamp.
gyro_still_det->last_sample_time = sample_time;
// Online window mean and variance ("one-pass" accumulation).
gyro_still_det->num_acc_win_samples++;
delta = (x - gyro_still_det->assumed_mean_x);
gyro_still_det->win_mean_x += delta;
gyro_still_det->acc_var_x += delta * delta;
delta = (y - gyro_still_det->assumed_mean_y);
gyro_still_det->win_mean_y += delta;
gyro_still_det->acc_var_y += delta * delta;
delta = (z - gyro_still_det->assumed_mean_z);
gyro_still_det->win_mean_z += delta;
gyro_still_det->acc_var_z += delta * delta;
}
// Calculates and returns the stillness confidence score [0,1].
float gyroStillDetCompute(struct GyroStillDet* gyro_still_det) {
float tmp_denom = 1.f;
float tmp_denom_mean = 1.f;
// Don't divide by zero (not likely, but a precaution).
if (gyro_still_det->num_acc_win_samples > 1) {
tmp_denom = 1.f / (gyro_still_det->num_acc_win_samples - 1);
tmp_denom_mean = 1.f / gyro_still_det->num_acc_win_samples;
} else {
// Return zero stillness confidence.
gyro_still_det->stillness_confidence = 0;
return gyro_still_det->stillness_confidence;
}
// Update the final calculation of window mean and variance.
float tmp = gyro_still_det->win_mean_x;
gyro_still_det->win_mean_x *= tmp_denom_mean;
gyro_still_det->win_var_x =
(gyro_still_det->acc_var_x - gyro_still_det->win_mean_x * tmp) *
tmp_denom;
tmp = gyro_still_det->win_mean_y;
gyro_still_det->win_mean_y *= tmp_denom_mean;
gyro_still_det->win_var_y =
(gyro_still_det->acc_var_y - gyro_still_det->win_mean_y * tmp) *
tmp_denom;
tmp = gyro_still_det->win_mean_z;
gyro_still_det->win_mean_z *= tmp_denom_mean;
gyro_still_det->win_var_z =
(gyro_still_det->acc_var_z - gyro_still_det->win_mean_z * tmp) *
tmp_denom;
// Adds the assumed mean value back to the total mean calculation.
gyro_still_det->win_mean_x += gyro_still_det->assumed_mean_x;
gyro_still_det->win_mean_y += gyro_still_det->assumed_mean_y;
gyro_still_det->win_mean_z += gyro_still_det->assumed_mean_z;
// Define the variance thresholds.
float upper_var_thresh =
(gyro_still_det->var_threshold + gyro_still_det->confidence_delta);
float lower_var_thresh =
(gyro_still_det->var_threshold - gyro_still_det->confidence_delta);
// Compute the stillness confidence score.
if ((gyro_still_det->win_var_x > upper_var_thresh) ||
(gyro_still_det->win_var_y > upper_var_thresh) ||
(gyro_still_det->win_var_z > upper_var_thresh)) {
// Sensor variance exceeds the upper threshold (i.e., motion detected).
// Set stillness confidence equal to 0.
gyro_still_det->stillness_confidence = 0;
} else {
if ((gyro_still_det->win_var_x <= lower_var_thresh) &&
(gyro_still_det->win_var_y <= lower_var_thresh) &&
(gyro_still_det->win_var_z <= lower_var_thresh)) {
// Sensor variance is below the lower threshold (i.e., stillness
// detected).
// Set stillness confidence equal to 1.
gyro_still_det->stillness_confidence = 1.f;
} else {
// Motion detection thresholds not exceeded. Compute the stillness
// confidence score.
float var_thresh = gyro_still_det->var_threshold;
// Compute the stillness confidence score.
// Each axis score is limited [0,1].
tmp_denom = 1.f / (upper_var_thresh - lower_var_thresh);
gyro_still_det->stillness_confidence =
gyroStillDetLimit(0.5f - (gyro_still_det->win_var_x - var_thresh) *
tmp_denom) *
gyroStillDetLimit(0.5f - (gyro_still_det->win_var_y - var_thresh) *
tmp_denom) *
gyroStillDetLimit(0.5f - (gyro_still_det->win_var_z - var_thresh) *
tmp_denom);
}
}
// Return the stillness confidence.
return gyro_still_det->stillness_confidence;
}
// Resets the stillness detector and initiates a new detection window.
// 'reset_stats' determines whether the stillness statistics are reset.
void gyroStillDetReset(struct GyroStillDet* gyro_still_det, bool reset_stats) {
float tmp_denom = 1.f;
// Reset the stillness data ready flag.
gyro_still_det->stillness_window_ready = false;
// Signal to start capture of next stillness data window.
gyro_still_det->start_new_window = true;
// Track the stillness confidence (current->previous).
gyro_still_det->prev_stillness_confidence =
gyro_still_det->stillness_confidence;
// Track changes in the mean estimate.
if (gyro_still_det->num_acc_samples > 1) {
tmp_denom = 1.f / gyro_still_det->num_acc_samples;
}
gyro_still_det->prev_mean_x = gyro_still_det->mean_x * tmp_denom;
gyro_still_det->prev_mean_y = gyro_still_det->mean_y * tmp_denom;
gyro_still_det->prev_mean_z = gyro_still_det->mean_z * tmp_denom;
// Reset the current statistics to zero.
if (reset_stats) {
gyro_still_det->num_acc_samples = 0;
gyro_still_det->mean_x = 0;
gyro_still_det->mean_y = 0;
gyro_still_det->mean_z = 0;
gyro_still_det->acc_var_x = 0;
gyro_still_det->acc_var_y = 0;
gyro_still_det->acc_var_z = 0;
}
}
// Enforces the limits of an input value [0,1].
float gyroStillDetLimit(float value) {
// Fix limits [0,1].
if (value < 0) {
value = 0;
} else {
if (value > 1.f) {
value = 1.f;
}
}
return value;
}