ardupilot/libraries/AP_HAL/DSP.h

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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
*/
/*
interface to DSP device
*/
#pragma once
#include <stdint.h>
#include "AP_HAL_Namespace.h"
#include <AP_HAL/utility/RingBuffer.h>
#define DSP_MEM_REGION AP_HAL::Util::MEM_FAST
// Maximum tolerated number of cycles with missing signal
#define FFT_MAX_MISSED_UPDATES 5
class AP_HAL::DSP {
#if HAL_WITH_DSP
public:
enum FrequencyPeak : uint8_t {
CENTER = 0,
LOWER_SHOULDER = 1,
UPPER_SHOULDER = 2,
MAX_TRACKED_PEAKS = 3,
NONE = 4
};
struct FrequencyPeakData {
// estimate of FFT peak frequency
float _freq_hz;
// FFT bin with maximum energy
uint16_t _bin;
// width of the peak
float _noise_width_hz;
};
static const uint8_t MAX_SLIDING_WINDOW_SIZE = 8;
class FFTWindowState {
public:
// frequency width of a FFT bin
const float _bin_resolution;
// number of FFT bins
const uint16_t _bin_count;
// number of stored frequencies (_bin_count + DC)
const uint16_t _num_stored_freqs;
// size of the FFT window
const uint16_t _window_size;
// size of the FFT sliding window
const uint8_t _sliding_window_size;
// FFT data
float* _freq_bins;
// derivative real data scratch space
float* _derivative_freq_bins;
// intermediate real FFT data
float* _rfft_data;
// averaged frequency data via Welch's method
float* _avg_freq_bins;
// sliding window of _bin_count frames
float* _sliding_window;
// three highest peaks
FrequencyPeakData _peak_data[MAX_TRACKED_PEAKS];
// Hanning window for incoming samples, see https://en.wikipedia.org/wiki/Window_function#Hann_.28Hanning.29_window
float* _hanning_window;
// Use in calculating the PS of the signal [Heinz] equations (20) & (21)
float _window_scale;
// averaging is ongoing
bool _averaging;
// number of samples in the average
uint32_t _averaging_samples;
// current sliding window slice
uint8_t _current_slice;
// get a frequency bin from an arbitrary slice
float get_freq_bin(uint16_t idx) { return _sliding_window == nullptr ? _freq_bins[idx] : _avg_freq_bins[idx]; }
void free_data_structures();
virtual ~FFTWindowState();
FFTWindowState(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size);
};
// initialise an FFT instance
virtual FFTWindowState* fft_init(uint16_t window_size, uint16_t sample_rate, uint8_t sliding_window_size = 0) = 0;
// start an FFT analysis with an ObjectBuffer
virtual void fft_start(FFTWindowState* state, FloatBuffer& samples, uint16_t advance) = 0;
// perform remaining steps of an FFT analysis
virtual uint16_t fft_analyse(FFTWindowState* state, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff) = 0;
// start averaging FFT data
bool fft_start_average(FFTWindowState* fft);
// finish the averaging process
uint16_t fft_stop_average(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin, float* peaks);
protected:
// step 3: find the magnitudes of the complex data
void step_cmplx_mag(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin, float noise_att_cutoff);
// calculate the noise width of a peak based on the input parameters
float find_noise_width(float* freq_bins, uint16_t start_bin, uint16_t end_bin, uint16_t max_energy_bin, float cutoff,
float bin_resolution, uint16_t& peak_top, uint16_t& peak_bottom) const;
// step 4: find the bin with the highest energy and interpolate the required frequency
uint16_t step_calc_frequencies(FFTWindowState* fft, uint16_t start_bin, uint16_t end_bin);
// calculate the final average output
void update_average_from_sliding_window(FFTWindowState* fft);
// calculate a single frequency
uint16_t calc_frequency(FFTWindowState* fft, uint16_t start_bin, uint16_t peak_bin, uint16_t end_bin);
// find the maximum value in an vector of floats
virtual void vector_max_float(const float* vin, uint16_t len, float* max_value, uint16_t* max_index) const = 0;
// find the mean value in an vector of floats
virtual float vector_mean_float(const float* vin, uint16_t len) const = 0;
// multiply an vector of floats by a scale factor
virtual void vector_scale_float(const float* vin, float scale, float* vout, uint16_t len) const = 0;
// add two vectors together
virtual void vector_add_float(const float* vin1, const float* vin2, float* vout, uint16_t len) const = 0;
// algorithm for finding peaks in noisy data as per https://terpconnect.umd.edu/~toh/spectrum/PeakFindingandMeasurement.htm
uint16_t find_peaks(const float* input, uint16_t length, float* output, uint16_t* peaks, uint16_t peaklen,
float slopeThreshold, float ampThreshold, uint16_t smoothwidth, uint16_t peakgroup) const;
uint16_t val2index(const float* vector, uint16_t n, float val) const;
void derivative(const float* input, float* output, uint16_t n) const;
void fastsmooth(float* input, uint16_t n, uint16_t smoothwidth) const;
// Quinn's frequency interpolator
float calculate_quinns_second_estimator(const FFTWindowState* fft, const float* complex_fft, uint16_t k) const;
float tau(const float x) const;
// Jain's estimator
float calculate_jains_estimator(const FFTWindowState* fft, const float* real_fft, uint16_t k_max);
// init averaging FFT data
bool fft_init_average(FFTWindowState* fft);
#endif // HAL_WITH_DSP
};