ardupilot/libraries/AP_HAL_SITL/DSP.cpp

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/*
* 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>
#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)
{
DSP::FFTWindowStateSITL* fft = new DSP::FFTWindowStateSITL(window_size, sample_rate);
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)
: AP_HAL::DSP::FFTWindowState::FFTWindowState(window_size, sample_rate)
{
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: performm 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;
}
}