I sent the signal generated with dsps_tone_gen_f32 through the serial port and graphed it in Excel. The graph looks like a sine wave, as expected. However, if I process the signal in Python and apply the FFT in Python, the result is also incorrect. So, how does dsps_tone_gen_f32 work?
According to the documentation, it appears as dsps_tone_gen_f32(float *output, int len, float Ampl, float freq, float phase), where freq is in terms of the Nyquist frequency. I understand that if I use dsps_tone_gen_f32(tone_2, N_buff, 5, 0.4, 0);, it corresponds to a 400 Hz signal. Is that correct?
Part of the data signal plot in excel
- imagen_2024-11-15_161746540.png (19.1 KiB) Viewed 800 times
- imagen_2024-11-15_162132622.png (6.52 KiB) Viewed 800 times
- imagen_2024-11-15_162341039.png (16.64 KiB) Viewed 800 times
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/*
* SPDX-FileCopyrightText: 2022 Espressif Systems (Shanghai) CO LTD
*
* SPDX-License-Identifier: Apache-2.0
*/
#include <stdio.h>
#include <stdlib.h>
#include "freertos/FreeRTOS.h"
#include "freertos/task.h"
#include "esp_system.h"
#include "driver/spi_master.h"
#include "soc/gpio_struct.h"
#include "driver/gpio.h"
#include "driver/uart.h"
#include "soc/uart_struct.h"
#include <math.h>
#include <malloc.h>
#include "esp_dsp.h"
static const char *TAG = "main";
// This example shows how to use FIR filters from esp-dsp library
#define FIR_COEFFS_LEN 64 // Number of FIR filter coefficients
#define DECIMATION 2 // Decimation ratio of the FIR filter
#define N_SAMPLES 1024 // Input samples
#define FIR_DELAY (FIR_COEFFS_LEN / DECIMATION) // Amount of samples not being considered for the FFT
#define FIR_BUFF_OUT_LEN (N_SAMPLES + FIR_DELAY) // Total length of samples
// Function shows the result of the FIR filter
void show_FFT(float *input_signal, const unsigned int fft_len)
{
dsps_fft2r_fc32(input_signal, fft_len >> 1);
dsps_bit_rev2r_fc32(input_signal, fft_len >> 1);
dsps_cplx2real_fc32(input_signal, fft_len >> 1);
// Correction factor for the FFT spectrum
const float correction_factor = fft_len * 3;
// Calculating power of spectrum in dB
for (int i = 0 ; i < fft_len / 2 ; i++) {
input_signal[i] = 10 * log10f((input_signal[i * 2 + 0] * input_signal[i * 2 + 0] + input_signal[i * 2 + 1] * input_signal[i * 2 + 1] + 0.0000001) / correction_factor);
}
// Display power spectrum
dsps_view(input_signal, fft_len / 2, 64, 10, -120, 40, '|');
}
// Generate Windowed-Sinc filter coefficients
void generate_FIR_coefficients(float *fir_coeffs, const unsigned int fir_len, const float ft)
{
// Even or odd length of the FIR filter
const bool is_odd = (fir_len % 2) ? (true) : (false);
const float fir_order = (float)(fir_len - 1);
// Window coefficients
float *fir_window = (float *)malloc(fir_len * sizeof(float));
dsps_wind_blackman_f32(fir_window, fir_len);
for (int i = 0; i < fir_len; i++) {
if ((i == fir_order / 2) && (is_odd)) {
fir_coeffs[i] = 2 * ft;
} else {
fir_coeffs[i] = sinf((2 * M_PI * ft * (i - fir_order / 2))) / (M_PI * (i - fir_order / 2));
}
fir_coeffs[i] *= fir_window[i];
}
free(fir_window);
}
void create_fir_notch(float *coeffs, int len, float notch_freq, float sample_rate) {
// Factor de normalización de frecuencia (0 a 0.5)
float ft = notch_freq / (sample_rate / 2);
// Generar una ventana para suavizar el filtro (Blackman es una buena elección)
float window[len];
dsps_wind_blackman_f32(window, len);
for (int i = 0; i < len; i++) {
// Fórmula para el filtro notch centrado en `notch_freq`
if (i == len / 2) {
coeffs[i] = 1.0 - 2.0 * ft;
} else {
coeffs[i] = -sin(2 * M_PI * ft * (i - len / 2)) / (M_PI * (i - len / 2));
}
coeffs[i] *= window[i]; // Aplicar ventana
}
}
static __attribute__((aligned(16))) float tone_combined[FIR_BUFF_OUT_LEN];
static __attribute__((aligned(16))) float fir_coeffs[FIR_COEFFS_LEN];
static __attribute__((aligned(16))) float delay_line[FIR_COEFFS_LEN];
void app_main()
{
const int32_t fir_len = FIR_COEFFS_LEN;
const float fir_ft = 0.5 / DECIMATION; // Transition frequency of the FIR filter
const int32_t N = N_SAMPLES; // Number of input samples
const int32_t fir_decim = DECIMATION; // FIR filter decimation
const int32_t N_buff = FIR_BUFF_OUT_LEN; // Total length of samples with ignored
fir_f32_t fir1;
esp_err_t ret;
// Ignoring the first set of samples, due to the delay line of the FIR filter
const int fir_out_offset = ((FIR_DELAY / 2) - 1);
ESP_LOGI(TAG, "Start Example.");
// If a user doesn't care about buffer allocation, the default
// initialization could be used as shown here:
ret = dsps_fft2r_init_fc32(NULL, CONFIG_DSP_MAX_FFT_SIZE);
if (ret != ESP_OK) {
ESP_LOGE(TAG, "Not possible to initialize FFT. Error = %i", ret);
return;
}
ret = dsps_fft4r_init_fc32(NULL, CONFIG_DSP_MAX_FFT_SIZE);
if (ret != ESP_OK) {
ESP_LOGE(TAG, "Not possible to initialize FFT. Error = %i", ret);
return;
}
// Generate input signal as 2 sine waves
//float *tone_1 = (float *)malloc(N_buff * sizeof(float));
float *tone_2 = (float *)malloc(N_buff * sizeof(float));
//dsps_tone_gen_f32(tone_1, N_buff, 5, 0.2, 0);
dsps_tone_gen_f32(tone_2, N_buff, 5, 0.4, 0);
// Generate windowing coefficients
float *window = (float *)malloc(N * sizeof(float));
dsps_wind_blackman_harris_f32(window, N);
// Add the two waves together
/*for (int i = 0 ; i < N_buff ; i++) {
tone_combined[i] = tone_2[i];
}
while(true){
for (int i = 0 ; i < N_buff ; i++) {
printf("%f\n", tone_combined[i]);
}
}
return;*/
//free(tone_1);
//free(tone_2);
// Apply the windowing
for (int i = 0 ; i < N ; i++) {
//window[i] *= tone_combined[i];
window[i] *= tone_2[i];
}
// Show FFT spectrum
show_FFT(window, N);
return;
// Calculate coefficients for the FIR filter
generate_FIR_coefficients(fir_coeffs, fir_len, fir_ft);
ESP_LOGI(TAG, "\n");
// Filter the input signal with FIR filter
float *fir_out = (float *)malloc( N_buff * sizeof(float));
dsps_fird_init_f32(&fir1, fir_coeffs, delay_line, fir_len, fir_decim);
uint32_t start_b = dsp_get_cpu_cycle_count();
dsps_fird_f32(&fir1, tone_combined, fir_out, N_buff / fir_decim);
uint32_t end_b = dsp_get_cpu_cycle_count();
// Generate windowing coefficients and apply the windowing
dsps_wind_blackman_harris_f32(window, (N / fir_decim));
for (int i = 0 ; i < N / fir_decim ; i++) {
window[i] *= fir_out[fir_out_offset + i];
}
// Show FFT spectrum, ignoring first samples from the delay line
show_FFT(window, N / fir_decim);
ESP_LOGI(TAG, "FIR for %"PRId32" samples and decimation %"PRId32" takes %"PRId32" cycles", N, fir_decim, (int32_t)(end_b - start_b));
ESP_LOGI(TAG, "End Example.");
free(fir_out);
free(window);
}