#include #include #include #include #include "common/wave.h" #include "ft8/pack.h" #include "ft8/encode.h" #include "ft8/pack_v2.h" #include "ft8/encode_v2.h" #include "ft8/ldpc.h" #include "fft/kiss_fftr.h" void usage() { printf("Decode a 15-second WAV file.\n"); } float hann_i(int i, int N) { float x = sinf((float)M_PI * i / (N - 1)); return x*x; } struct Candidate { int16_t score; uint16_t time_offset; uint16_t freq_offset; uint8_t time_sub; uint8_t freq_sub; }; void heapify_down(Candidate * heap, int heap_size) { // heapify from the root down int current = 0; while (true) { int largest = current; int left = 2 * current + 1; int right = left + 1; if (left < heap_size && heap[left].score < heap[largest].score) { largest = left; } if (right < heap_size && heap[right].score < heap[largest].score) { largest = right; } if (largest == current) { break; } Candidate tmp = heap[largest]; heap[largest] = heap[current]; heap[current] = tmp; current = largest; } } void heapify_up(Candidate * heap, int heap_size) { // heapify from the last node up int current = heap_size - 1; while (current > 0) { int parent = (current - 1) / 2; if (heap[current].score >= heap[parent].score) { break; } Candidate tmp = heap[parent]; heap[parent] = heap[current]; heap[current] = tmp; current = parent; } } // Find top N candidates in frequency and time according to their sync strength (looking at Costas symbols) void find_sync(const uint8_t * power, int num_blocks, int num_bins, int num_candidates, Candidate * heap) { // Costas 7x7 tone pattern const uint8_t ICOS7[] = { 2,5,6,0,4,1,3 }; int heap_size = 0; for (int alt = 0; alt < 4; ++alt) { for (int time_offset = 0; time_offset < num_blocks - NN; ++time_offset) { for (int freq_offset = 0; freq_offset < num_bins - 8; ++freq_offset) { int score = 0; // Compute score over bins 0-7, 36-43, 72-79 for (int m = 0; m <= 72; m += 36) { for (int k = 0; k < 7; ++k) { int offset = ((time_offset + k + m) * 4 + alt) * num_bins + freq_offset; // score += 8 * (int)power[time_offset + k + m][alt][freq_offset + ICOS7[k]] - score += 8 * (int)power[offset + ICOS7[k]] - power[offset + 0] - power[offset + 1] - power[offset + 2] - power[offset + 3] - power[offset + 4] - power[offset + 5] - power[offset + 6] - power[offset + 7]; } } // update the candidate list if (heap_size == num_candidates && score > heap[0].score) { // extract the least promising candidate heap[0] = heap[heap_size - 1]; --heap_size; heapify_down(heap, heap_size); } if (heap_size < num_candidates) { // add the current candidate heap[heap_size].score = score; heap[heap_size].time_offset = time_offset; heap[heap_size].freq_offset = freq_offset; heap[heap_size].time_sub = alt / 2; heap[heap_size].freq_sub = alt % 2; ++heap_size; heapify_up(heap, heap_size); } } } } } // Compute FFT magnitudes (log power) for each timeslot in the signal void extract_power(const float * signal, int num_blocks, int num_bins, uint8_t * power) { const int block_size = 2 * num_bins; // Average over 2 bins per FSK tone const int nfft = 2 * block_size; // We take FFT of two blocks, advancing by one float window[nfft]; for (int i = 0; i < nfft; ++i) { window[i] = hann_i(i, nfft); } size_t fft_work_size; kiss_fftr_alloc(nfft, 0, 0, &fft_work_size); printf("N_FFT = %d\n", nfft); printf("FFT work area = %lu\n", fft_work_size); void * fft_work = malloc(fft_work_size); kiss_fftr_cfg fft_cfg = kiss_fftr_alloc(nfft, 0, fft_work, &fft_work_size); int offset = 0; float fft_norm = 1.0f / nfft; for (int i = 0; i < num_blocks; ++i) { // Loop over two possible time offsets (0 and block_size/2) for (int time_sub = 0; time_sub <= block_size/2; time_sub += block_size/2) { kiss_fft_scalar timedata[nfft]; kiss_fft_cpx freqdata[nfft/2 + 1]; float mag_db[nfft/2 + 1]; // Extract windowed signal block for (int j = 0; j < nfft; ++j) { timedata[j] = window[j] * signal[(i * block_size) + (j + time_sub)]; } kiss_fftr(fft_cfg, timedata, freqdata); // Compute log magnitude in decibels for (int j = 0; j < nfft/2 + 1; ++j) { float mag2 = fft_norm * (freqdata[j].i * freqdata[j].i + freqdata[j].r * freqdata[j].r); mag_db[j] = 10.0f * log10f(1.0E-10f + mag2); } // Loop over two possible frequency bin offsets (for averaging) for (int freq_sub = 0; freq_sub < 2; ++freq_sub) { for (int j = 0; j < num_bins; ++j) { float db1 = mag_db[j * 2 + freq_sub]; float db2 = mag_db[j * 2 + freq_sub + 1]; float db = (db1 + db2) / 2; // Scale decibels to unsigned 8-bit range int scaled = (int)(0.5f + 2 * (db + 100)); power[offset] = (scaled < 0) ? 0 : ((scaled > 255) ? 255 : scaled); ++offset; } } } } free(fft_work); } int main(int argc, char ** argv) { // Expect one command-line argument if (argc < 2) { usage(); return -1; } const char * wav_path = argv[1]; int sample_rate = 12000; int num_samples = 15 * sample_rate; float signal[num_samples]; int rc = load_wav(signal, num_samples, sample_rate, wav_path); if (rc < 0) { return -1; } const float fsk_dev = 6.25f; const int num_bins = (int)(sample_rate / (2 * fsk_dev)); const int block_size = 2 * num_bins; const int num_blocks = (num_samples - (block_size/2) - block_size) / block_size; uint8_t power[num_blocks * 4 * num_bins]; // [num_blocks][4][num_bins] ~ 200 KB printf("%d blocks, %d bins\n", num_blocks, num_bins); extract_power(signal, num_blocks, num_bins, power); const int num_candidates = 250; Candidate heap[num_candidates]; find_sync(power, num_blocks, num_bins, num_candidates, heap); for (int i = 0; i < num_candidates; ++i) { float freq_offset = (heap[i].freq_offset + heap[i].freq_sub / 2.0f) * fsk_dev; float time_offset = (heap[i].time_offset + heap[i].time_sub / 2.0f) / fsk_dev; // int offset = (heap[i].time_offset * 4 + heap[i].time_sub * 2 + heap[i].freq_sub) * num_bins + heap[i].freq_offset; printf("%03d: score = %.1f freq = %.1f time = %.2f\n", i, heap[i].score / 7.0f / 2, freq_offset, time_offset); } /* // take absolute magnitude s2(0:7,k)=abs(csymb(1:8))/1e3 // skip Costas sync symbols s1(0:7,j)=s2(0:7,k) // Normalize by median magnitude s1=s1/xmeds1 // Extract bit significance ps=s1(0:7,j) bmeta(i4)=max(ps(4),ps(5),ps(6),ps(7))-max(ps(0),ps(1),ps(2),ps(3)) bmeta(i2)=max(ps(2),ps(3),ps(6),ps(7))-max(ps(0),ps(1),ps(4),ps(5)) bmeta(i1)=max(ps(1),ps(3),ps(5),ps(7))-max(ps(0),ps(2),ps(4),ps(6)) // Normalize by std. deviation call normalizebmet(bmeta,3*ND) // Magical fudge/scale factor scalefac=2.83 llr0=scalefac*bmeta */ return 0; }