I have a BEAUTIFUL doppler radar signal here from a 24.050-24.250 GHZ sensor measuring a very small object at 143 fps speed (speed from another 10 GHZ radar) in a measuring area of about 300mm-500mm in front of the sensor(s). The signal was limited to around 3V with a zener diode.
I took several measurements (at this speed and object size and distance from the sensors) and there were about 8-20 wave peaks on the average from above the trigger threshold level (2.58V) until the end of the trigger threshold level box where the peaks start falling off.
Looking at the graph, one can discard the first 3 peaks and the last 2-3 peaks above the trigger threshold which leaves a decent area (orange box) for sampling of the peaks for frequency/period. So in this case we have about 17 "good" peaks inside the orange box to be measured. In this case the orange box (measuring sample area) is 5 x 500 us = 2500 us in length.
I know that an FFT would be the best way to measure, but the one FFT program I used with Arduino gave me inconsistent results. Not sure how to set the sample size (must be in power of 2 increment from 2 to 256). And the maximum sampling frequency is 10kHz (hardware limitations).
I set sample sizes to 4 and 16 and 128 at 10Khz frequency, but get inconsistent results. I suspect logarithmic results, but even those do not add up. Sometime I get within 2-3% but at times it's off by 30% with no apparent correlation.
What I know:
- with this 24 GHZ radar (no angles) the speed = frequency / 44 to arrive to km/h
- in this case the o-scope measured 6613 Hz with a 151.2 us period, but that was for the entire area above the 2.58V trigger threshold. But it also had some much more varying readings as noticeable in the first 2-3 peaks after the trigger and the last 2-3 peaks that are falling off to below the trigger threshold. I excluded these from the orange box.
How do I set up this FFT, or another FFT, or similar method, that would determine the dominant frequency from data inside the orange box? The orange box sample size will always seems to be between the 8-20 number of peaks range. I measured frequency and periods from "positive rising edge to positive rising edge".
I tried with an Adafruit nRF52840 Express (16 Mhz clock) and an Adafruit 32u4 Bluefruit (8 Mhz clock).
I am using this Arduino FFT library: GitHub - kosme/arduinoFFT: Fast Fourier Transform for Arduino
Some broad info about this FFT itself: What Is FFT and How Can You Implement It on an Arduino? – Norwegian Creations
Thank you.
#include "arduinoFFT.h"
#define SAMPLES 4 //Must be a power of 2 128, 256?
#define SAMPLING_FREQUENCY 10000 //Hz, must be less than 10000 due to ADC
arduinoFFT FFT = arduinoFFT();
unsigned int sampling_period_us;
unsigned long microseconds;
double vReal[SAMPLES];
double vImag[SAMPLES];
void setup() {
Serial.begin(115200);
sampling_period_us = round(1000000*(1.0/SAMPLING_FREQUENCY));
}
void loop() {
if (analogRead(A0) >600) {
/*SAMPLING*/
for(int i=0; i<SAMPLES; i++)
{
microseconds = micros(); //Overflows after around 70 minutes!
vReal[i] = analogRead(A0);
vImag[i] = 0;
while(micros() < (microseconds + sampling_period_us)){
}
}
/*FFT*/
FFT.Windowing(vReal, SAMPLES, FFT_WIN_TYP_HAMMING, FFT_FORWARD);
FFT.Compute(vReal, vImag, SAMPLES, FFT_FORWARD);
FFT.ComplexToMagnitude(vReal, vImag, SAMPLES);
double peak = FFT.MajorPeak(vReal, SAMPLES, SAMPLING_FREQUENCY);
/*PRINT RESULTS*/
Serial.println(peak); //Print out what frequency is the most dominant.
// for(int i=0; i<(SAMPLES/2); i++)
// {
/*View all these three lines in serial terminal to see which frequencies has which amplitudes*/
//Serial.print((i * 1.0 * SAMPLING_FREQUENCY) / SAMPLES, 1);
//Serial.print(" ");
// Serial.println(vReal[i], 1); //View only this line in serial plotter to visualize the bins
// }
}
//delay(1000); //Repeat the process every second OR:
// while(1); //Run code once
}
