mirror of https://github.com/ArduPilot/ardupilot
304 lines
11 KiB
C++
304 lines
11 KiB
C++
/*
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* This file is free software: you can redistribute it and/or modify it
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* under the terms of the GNU General Public License as published by the
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* Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This file is distributed in the hope that it will be useful, but
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* WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
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* See the GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License along
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* with this program. If not, see <http://www.gnu.org/licenses/>.
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*
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* Code by Andy Piper and the betaflight team
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*/
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#include "AP_HAL_ChibiOS.h"
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#if HAL_WITH_DSP
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#include <AP_HAL/AP_HAL.h>
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#include <AP_Math/AP_Math.h>
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#include <GCS_MAVLink/GCS.h>
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#include "DSP.h"
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#include <cmath>
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using namespace ChibiOS;
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#if DEBUG_FFT
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#define TIMER_START(timer) \
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void *istate = hal.scheduler->disable_interrupts_save(); \
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uint32_t timer##now = AP_HAL::micros()
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#define TIMER_END(timer) timer.time(timer##now); \
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hal.scheduler->restore_interrupts(istate)
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#else
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#define TIMER_START(timer)
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#define TIMER_END(timer)
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#endif
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#define TICK_CYCLE 10
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extern const AP_HAL::HAL& hal;
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// The algorithms originally came from betaflight but are now substantially modified based on theory and experiment.
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// https://holometer.fnal.gov/GH_FFT.pdf "Spectrum and spectral density estimation by the Discrete Fourier transform (DFT),
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// including a comprehensive list of window functions and some new flat-top windows." - Heinzel et. al is a great reference
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// for understanding the underlying theory although we do not use spectral density here since time resolution is equally
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// important as frequency resolution. Referred to as [Heinz] throughout the code.
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// initialize the FFT state machine
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AP_HAL::DSP::FFTWindowState* DSP::fft_init(uint16_t window_size, uint16_t sample_rate, uint8_t harmonics)
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{
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DSP::FFTWindowStateARM* fft = new DSP::FFTWindowStateARM(window_size, sample_rate, harmonics);
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if (fft == nullptr || fft->_hanning_window == nullptr || fft->_rfft_data == nullptr || fft->_freq_bins == nullptr || fft->_derivative_freq_bins == nullptr) {
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delete fft;
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return nullptr;
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}
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return fft;
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}
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// start an FFT analysis
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void DSP::fft_start(FFTWindowState* state, FloatBuffer& samples, uint16_t advance)
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{
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step_hanning((FFTWindowStateARM*)state, samples, advance);
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}
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// perform remaining steps of an FFT analysis
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uint16_t DSP::fft_analyse(AP_HAL::DSP::FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff)
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{
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FFTWindowStateARM* fft = (FFTWindowStateARM*)state;
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step_arm_cfft_f32(fft);
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step_bitreversal(fft);
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step_stage_rfft_f32(fft);
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step_arm_cmplx_mag_f32(fft, start_bin, end_bin, noise_att_cutoff);
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return step_calc_frequencies_f32(fft, start_bin, end_bin);
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}
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// create an instance of the FFT state machine
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DSP::FFTWindowStateARM::FFTWindowStateARM(uint16_t window_size, uint16_t sample_rate, uint8_t harmonics)
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: AP_HAL::DSP::FFTWindowState::FFTWindowState(window_size, sample_rate, harmonics)
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{
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if (_freq_bins == nullptr || _hanning_window == nullptr || _rfft_data == nullptr || _derivative_freq_bins == nullptr) {
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GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "Failed to allocate %u bytes for window %u for DSP",
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unsigned(sizeof(float) * (window_size * 3 + 2)), unsigned(window_size));
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return;
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}
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// initialize the ARM data structure.
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// it's important not to use arm_rfft_fast_init_f32() as this links all of the twiddle tables
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// by being selective we save 70k in text space
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switch (window_size) {
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case 32:
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arm_rfft_32_fast_init_f32(&_fft_instance);
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break;
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case 64:
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arm_rfft_64_fast_init_f32(&_fft_instance);
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break;
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case 128:
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arm_rfft_128_fast_init_f32(&_fft_instance);
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break;
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case 256:
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arm_rfft_256_fast_init_f32(&_fft_instance);
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break;
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#if defined(STM32H7)
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// Don't pull in the larger FFT tables unless we have to
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case 512:
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arm_rfft_512_fast_init_f32(&_fft_instance);
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break;
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case 1024:
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arm_rfft_1024_fast_init_f32(&_fft_instance);
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break;
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#endif
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}
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}
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DSP::FFTWindowStateARM::~FFTWindowStateARM() {}
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extern "C" {
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void stage_rfft_f32(arm_rfft_fast_instance_f32 *S, float32_t *p, float32_t *pOut);
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void arm_cfft_radix8by2_f32(arm_cfft_instance_f32 *S, float32_t *p1);
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void arm_cfft_radix8by4_f32(arm_cfft_instance_f32 *S, float32_t *p1);
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void arm_radix8_butterfly_f32(float32_t *pSrc, uint16_t fftLen, const float32_t *pCoef, uint16_t twidCoefModifier);
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void arm_bitreversal_32(uint32_t *pSrc, const uint16_t bitRevLen, const uint16_t *pBitRevTable);
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}
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// step 1: filter the incoming samples through a Hanning window
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void DSP::step_hanning(FFTWindowStateARM* fft, FloatBuffer& samples, uint16_t advance)
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{
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TIMER_START(_hanning_timer);
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// 5us
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// apply hanning window to gyro samples and store result in _freq_bins
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// hanning starts and ends with 0, could be skipped for minor speed improvement
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samples.peek(&fft->_freq_bins[0], fft->_window_size); // the caller ensures we get a full buffer of samples
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samples.advance(advance);
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arm_mult_f32(&fft->_freq_bins[0], &fft->_hanning_window[0], &fft->_freq_bins[0], fft->_window_size);
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TIMER_END(_hanning_timer);
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}
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// step 2: guts of complex fft processing
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void DSP::step_arm_cfft_f32(FFTWindowStateARM* fft)
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{
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arm_cfft_instance_f32 *Sint = &(fft->_fft_instance.Sint);
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Sint->fftLen = fft->_fft_instance.fftLenRFFT / 2;
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TIMER_START(_arm_cfft_f32_timer);
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switch (fft->_bin_count) {
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case 16: // window 32
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// 16us (BF)
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// 5us F7, 7us F4, 8us H7
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case 128: // window 256
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// 37us F7, 81us F4, 17us H7
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arm_cfft_radix8by2_f32(Sint, fft->_freq_bins);
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break;
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case 32: // window 64
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// 35us (BF)
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// 10us F7, 24us F4
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case 256: // window 512
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// 66us F7, 174us F4, 37us H7
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arm_cfft_radix8by4_f32(Sint, fft->_freq_bins);
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break;
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case 64: // window 128
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// 70us BF
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// 21us F7, 34us F4
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case 512: // window 1024
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// 152us F7, 73us H7
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arm_radix8_butterfly_f32(fft->_freq_bins, fft->_bin_count, Sint->pTwiddle, 1);
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break;
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}
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TIMER_END(_arm_cfft_f32_timer);
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}
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// step 3: reverse the bits of the output
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void DSP::step_bitreversal(FFTWindowStateARM* fft)
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{
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TIMER_START(_bitreversal_timer);
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// 6us (BF)
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// 32 - 2us F7, 3us F4, 1us H7
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// 64 - 3us F7, 6us F4
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// 128 - 4us F7, 9us F4
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// 256 - 10us F7, 20us F4, 5us H7
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// 512 - 22us F7, 54us F4, 15us H7
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// 1024 - 42us F7, 15us H7
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arm_bitreversal_32((uint32_t *)fft->_freq_bins, fft->_fft_instance.Sint.bitRevLength, fft->_fft_instance.Sint.pBitRevTable);
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TIMER_END(_bitreversal_timer);
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}
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// step 4: convert from complex to real data
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void DSP::step_stage_rfft_f32(FFTWindowStateARM* fft)
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{
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TIMER_START(_stage_rfft_f32_timer);
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// 14us (BF)
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// 32 - 2us F7, 5us F4, 2us H7
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// 64 - 5us F7, 16us F4
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// 128 - 17us F7, 26us F4
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// 256 - 21us F7, 70us F4, 9us H7
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// 512 - 35us F7, 71us F4, 17us H7
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// 1024 - 76us F7, 33us H7
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// this does not work in place => _freq_bins AND _rfft_data needed
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stage_rfft_f32(&fft->_fft_instance, fft->_freq_bins, fft->_rfft_data);
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TIMER_END(_stage_rfft_f32_timer);
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}
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// step 5: find the magnitudes of the complex data
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void DSP::step_arm_cmplx_mag_f32(FFTWindowStateARM* fft, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff)
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{
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TIMER_START(_arm_cmplx_mag_f32_timer);
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// 8us (BF)
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// 32 - 4us F7, 5us F4, 5us H7
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// 64 - 7us F7, 13us F4
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// 128 - 14us F7, 17us F4
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// 256 - 29us F7, 28us F4, 7us H7
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// 512 - 55us F7, 93us F4, 13us H7
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// 1024 - 131us F7, 25us H7
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// General case for the magnitudes - see https://stackoverflow.com/questions/42299932/dsp-libraries-rfft-strange-results
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// The frequency of each of those frequency components are given by k*fs/N
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arm_cmplx_mag_squared_f32(&fft->_rfft_data[2], &fft->_freq_bins[1], fft->_bin_count - 1);
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fft->_freq_bins[0] = sq(fft->_rfft_data[0]); // DC
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fft->_freq_bins[fft->_bin_count] = sq(fft->_rfft_data[1]); // Nyquist
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fft->_rfft_data[fft->_window_size] = fft->_rfft_data[1]; // Nyquist for the interpolator
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fft->_rfft_data[fft->_window_size + 1] = 0;
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step_cmplx_mag(fft, start_bin, end_bin, noise_att_cutoff);
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TIMER_END(_arm_cmplx_mag_f32_timer);
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}
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// step 6: find the bin with the highest energy and interpolate the required frequency
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uint16_t DSP::step_calc_frequencies_f32(FFTWindowStateARM* fft, uint16_t start_bin, uint16_t end_bin)
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{
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TIMER_START(_step_calc_frequencies);
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// 4us H7
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step_calc_frequencies(fft, start_bin, end_bin);
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TIMER_END(_step_calc_frequencies);
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#if DEBUG_FFT
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_output_count++;
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// outputs at approx 1hz
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if (_output_count % 400 == 0) {
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GCS_SEND_TEXT(MAV_SEVERITY_WARNING, "FFT(us): t1:%lu,t2:%lu,t3:%lu,t4:%lu,t5:%lu,t6:%lu",
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_hanning_timer._timer_avg, _arm_cfft_f32_timer._timer_avg, _bitreversal_timer._timer_avg, _stage_rfft_f32_timer._timer_avg, _arm_cmplx_mag_f32_timer._timer_avg, _step_calc_frequencies._timer_avg);
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}
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#endif
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return fft->_peak_data[CENTER]._bin;
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}
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static const float PI_N = M_PI / 32.0f;
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static const float CANDAN_FACTOR = tanf(PI_N) / PI_N;
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// Interpolate center frequency using http://users.metu.edu.tr/ccandan//pub_dir/FineDopplerEst_IEEE_SPL_June2011.pdf
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// This is slightly less accurate than Quinn, but much cheaper to calculate
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float DSP::calculate_candans_estimator(const FFTWindowStateARM* fft, uint16_t k_max) const
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{
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if (k_max <= 1 || k_max == fft->_bin_count) {
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return 0.0f;
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}
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const uint16_t k_m1 = (k_max - 1) * 2;
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const uint16_t k_p1 = (k_max + 1) * 2;
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const uint16_t k = k_max * 2;
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const float npr = fft->_rfft_data[k_m1] - fft->_rfft_data[k_p1];
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const float npc = fft->_rfft_data[k_m1 + 1] - fft->_rfft_data[k_p1 + 1];
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const float dpr = 2.0f * fft->_rfft_data[k] - fft->_rfft_data[k_m1] - fft->_rfft_data[k_p1];
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const float dpc = 2.0f * fft->_rfft_data[k + 1] - fft->_rfft_data[k_m1 + 1] - fft->_rfft_data[k_p1 + 1];
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const float realn = npr * dpr + npc * dpc;
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const float reald = dpr * dpr + dpc * dpc;
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// sanity check
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if (is_zero(reald)) {
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return 0.0f;
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}
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float d = CANDAN_FACTOR * (realn / reald);
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// -0.5 < d < 0.5 which is the fraction of the sample spacing about the center element
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return constrain_float(d, -0.5f, 0.5f);
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}
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#if DEBUG_FFT
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void DSP::StepTimer::time(uint32_t start)
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{
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_timer_total += (AP_HAL::micros() - start);
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_time_ticks = (_time_ticks + 1) % TICK_CYCLE;
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if (_time_ticks == 0) {
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_timer_avg = _timer_total / TICK_CYCLE;
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_timer_total = 0;
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}
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}
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#endif
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#endif
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