ardupilot/libraries/AP_HAL_SITL/DSP.cpp

216 lines
7.1 KiB
C++
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

/*
* This file is free software: you can redistribute it and/or modify it
* under the terms of the GNU General Public License as published by the
* Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This file is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
* See the GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along
* with this program. If not, see <http://www.gnu.org/licenses/>.
*
* Code by Andy Piper
*/
#include <AP_HAL/AP_HAL.h>
#if HAL_WITH_DSP
#include "AP_HAL_SITL.h"
#include <AP_Math/AP_Math.h>
#include <GCS_MAVLink/GCS.h>
#include "DSP.h"
#include <cmath>
#include <assert.h>
using namespace HALSITL;
extern const AP_HAL::HAL& hal;
// The algorithms originally came from betaflight but are now substantially modified based on theory and experiment.
// https://holometer.fnal.gov/GH_FFT.pdf "Spectrum and spectral density estimation by the Discrete Fourier transform (DFT),
// including a comprehensive list of window functions and some new flat-top windows." - Heinzel et. al is a great reference
// for understanding the underlying theory although we do not use spectral density here since time resolution is equally
// important as frequency resolution. Referred to as [Heinz] throughout the code.
// initialize the FFT state machine
AP_HAL::DSP::FFTWindowState* DSP::fft_init(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size)
{
DSP::FFTWindowStateSITL* fft = new DSP::FFTWindowStateSITL(window_size, sample_rate, sliding_window_size);
if (fft == nullptr || fft->_hanning_window == nullptr || fft->_rfft_data == nullptr || fft->_freq_bins == nullptr || fft->_derivative_freq_bins == nullptr) {
delete fft;
return nullptr;
}
return fft;
}
// start an FFT analysis
void DSP::fft_start(AP_HAL::DSP::FFTWindowState* state, FloatBuffer& samples, uint16_t advance)
{
step_hanning((FFTWindowStateSITL*)state, samples, advance);
}
// perform remaining steps of an FFT analysis
uint16_t DSP::fft_analyse(AP_HAL::DSP::FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff)
{
FFTWindowStateSITL* fft = (FFTWindowStateSITL*)state;
step_fft(fft);
step_cmplx_mag(fft, start_bin, end_bin, noise_att_cutoff);
return step_calc_frequencies(fft, start_bin, end_bin);
}
// create an instance of the FFT state machine
DSP::FFTWindowStateSITL::FFTWindowStateSITL(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size)
: AP_HAL::DSP::FFTWindowState::FFTWindowState(window_size, sample_rate, sliding_window_size)
{
if (_freq_bins == nullptr || _hanning_window == nullptr || _rfft_data == nullptr || _derivative_freq_bins == nullptr) {
GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "Failed to allocate window for DSP");
return;
}
buf = new complexf[window_size];
}
DSP::FFTWindowStateSITL::~FFTWindowStateSITL()
{
delete[] buf;
}
// step 1: filter the incoming samples through a Hanning window
void DSP::step_hanning(FFTWindowStateSITL* fft, FloatBuffer& samples, uint16_t advance)
{
// 5us
// apply hanning window to gyro samples and store result in _freq_bins
// hanning starts and ends with 0, could be skipped for minor speed improvement
uint32_t read_window = samples.peek(&fft->_freq_bins[0], fft->_window_size);
if (read_window != fft->_window_size) {
return;
}
samples.advance(advance);
mult_f32(&fft->_freq_bins[0], &fft->_hanning_window[0], &fft->_freq_bins[0], fft->_window_size);
}
// step 2: perform an in-place FFT on the windowed data
void DSP::step_fft(FFTWindowStateSITL* fft)
{
for (uint16_t i = 0; i < fft->_window_size; i++) {
fft->buf[i] = complexf(fft->_freq_bins[i], 0);
}
calculate_fft(fft->buf, fft->_window_size);
for (uint16_t i = 0; i < fft->_bin_count; i++) {
fft->_freq_bins[i] = std::norm(fft->buf[i]);
}
// components at the nyquist frequency are real only
for (uint16_t i = 0, j = 0; i <= fft->_bin_count; i++, j += 2) {
fft->_rfft_data[j] = fft->buf[i].real();
fft->_rfft_data[j+1] = fft->buf[i].imag();
}
}
void DSP::mult_f32(const float* v1, const float* v2, float* vout, uint16_t len)
{
for (uint16_t i = 0; i < len; i++) {
vout[i] = v1[i] * v2[i];
}
}
void DSP::vector_max_float(const float* vin, uint16_t len, float* maxValue, uint16_t* maxIndex) const
{
*maxValue = vin[0];
*maxIndex = 0;
for (uint16_t i = 1; i < len; i++) {
if (vin[i] > *maxValue) {
*maxValue = vin[i];
*maxIndex = i;
}
}
}
void DSP::vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const
{
for (uint16_t i = 0; i < len; i++) {
vout[i] = vin[i] * scale;
}
}
void DSP::vector_add_float(const float* vin1, const float* vin2, float* vout, uint16_t len) const
{
for (uint16_t i = 0; i < len; i++) {
vout[i] = vin1[i] + vin2[i];
}
}
float DSP::vector_mean_float(const float* vin, uint16_t len) const
{
float mean_value = 0.0f;
for (uint16_t i = 0; i < len; i++) {
mean_value += vin[i];
}
mean_value /= len;
return mean_value;
}
// simple integer log2
static uint16_t fft_log2(uint16_t n)
{
uint16_t k = n, i = 0;
while (k) {
k >>= 1;
i++;
}
return i - 1;
}
// calculate the in-place FFT of the input using the CooleyTukey algorithm
// this is a translation of Ron Nicholson's version in http://www.nicholson.com/dsp.fft1.html
void DSP::calculate_fft(complexf *samples, uint16_t fftlen)
{
uint16_t m = fft_log2(fftlen);
// shuffle data using bit reversed addressing ***
for (uint16_t k = 0; k < fftlen; k++) {
// generate a bit reversed address for samples[k] ***
uint16_t ki = k, kr = 0;
for (uint16_t i=1; i<=m; i++) {
kr <<= 1; // left shift result kr by 1 bit
if (ki % 2 == 1) {
kr++;
}
ki >>= 1; // right shift temp ki by 1 bit
}
// swap data samples[k] to bit reversed address samples[kr]
if (kr > k) {
complexf t = samples[kr];
samples[kr] = samples[k];
samples[k] = t;
}
}
// do fft butterflys in place
uint16_t istep = 2;
while (istep <= fftlen) {// layers 2,4,8,16, ... ,n
uint16_t is2 = istep / 2;
uint16_t astep = fftlen / istep;
for (uint16_t km = 0; km < is2; km++) { // outer row loop
uint16_t a = km * astep; // twiddle angle index
complexf w(sinf(2 * M_PI * (a+(fftlen/4)) / fftlen), sinf(2 * M_PI * a / fftlen));
for (uint16_t ki = 0; ki <= (fftlen - istep); ki += istep) { // inner column loop
uint16_t i = km + ki;
uint16_t j = is2 + i;
complexf t = w * samples[j];
complexf q = samples[i];
samples[j] = q - t;
samples[i] = q + t;
}
}
istep <<= 1;
}
}
#endif