1 files changed, 180 insertions, 0 deletions
diff --git a/controller/fw/src/dsss_demod.c b/controller/fw/src/dsss_demod.c
new file mode 100644
index 0000000..ec54d41
--- /dev/null
+++ b/controller/fw/src/dsss_demod.c
@@ -0,0 +1,180 @@
+
+#include <unistd.h>
+#include <stdbool.h>
+#include <math.h>
+
+#include <arm_math.h>
+
+#include "freq_meas.h"
+#include "sr_global.h"
+#include "dsss_demod.h"
+#include "simulation.h"
+
+#include "generated/dsss_gold_code.h"
+
+/* Generated CWT wavelet LUT */
+extern const float * const dsss_cwt_wavelet_table;
+
+struct iir_biquad cwt_filter_bq[3] = {
+    {.a = {-1.993939440f, 0.993949280f}, .b = {0.2459934300683e-5, 0.4919868601367e-5, 0.2459934300683e-5}},
+    {.a = {-1.995557124f, 0.995566972f}, .b = {0.2461930046414e-5, 0.4923860092828e-5, 0.2461930046414e-5}},
+    {.a = {-1.998365254f, 0.998375115f}, .b = {0.2465394452097e-5, 0.4930788904195e-5, 0.2465394452097e-5}},
+};
+
+float gold_correlate_step(const size_t ncode, const float a[DSSS_CORRELATION_LENGTH], size_t offx);
+float cwt_convolve_step(const float v[DSSS_WAVELET_LUT_SIZE], size_t offx);
+float run_iir(const float x, const int order, const struct iir_biquad q[order], struct iir_biquad_state st[order]);
+float run_biquad(float x, const struct iir_biquad *const q, struct iir_biquad_state *const restrict st);
+
+#ifdef SIMULATION
+void dsss_demod_step(struct dsss_demod_state *st, float new_value, size_t sim_pos) {
+#else /* SIMULATION */
+void dsss_demod_step(struct dsss_demod_state *st, float new_value) {
+#endif /* SIMULATION */
+
+//#define DEBUG_PRINT(...) ((void)0)
+//#define DEBUG_PRINTN(...) ((void)0)
+    bool debug = sim_pos % DSSS_CORRELATION_LENGTH == 0;
+    if (debug) DEBUG_PRINT("Iteration %zd", sim_pos);
+    //const float peak_group_threshold = 0.05 * DSSS_CORRELATION_LENGTH;
+    //const float hole_patching_threshold = 0.01 * DSSS_CORRELATION_LENGTH;
+
+    st->signal[st->signal_wpos] = new_value;
+    st->signal_wpos = (st->signal_wpos + 1) % ARRAY_LENGTH(st->signal);
+    if (debug) DEBUG_PRINT("   signal: %f", new_value);
+
+    /* use new, incremented wpos for gold_correlate_step as first element of old data in ring buffer */
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        st->correlation[i][st->correlation_wpos] = gold_correlate_step(i, st->signal, st->correlation_wpos);
+    /* debug */
+    /*
+    DEBUG_PRINTN("    correlation: [");
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        DEBUG_PRINTN("%f, ", st->correlation[i][st->correlation_wpos]);
+    DEBUG_PRINTN("]\n");
+    */
+    /* end */
+    st->correlation_wpos = (st->correlation_wpos + 1) % ARRAY_LENGTH(st->correlation[0]);
+
+    float cwt[DSSS_GOLD_CODE_COUNT];
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        cwt[i] = cwt_convolve_step(st->correlation[i], st->correlation_wpos);
+    /* debug */
+    if (debug) DEBUG_PRINTN("    cwt: [");
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        if (debug) DEBUG_PRINTN("%f, ", cwt[i]);
+    if (debug) DEBUG_PRINTN("]\n");
+    /* end */
+
+    float avg[DSSS_GOLD_CODE_COUNT];
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        avg[i] = run_iir(fabs(cwt[i]), ARRAY_LENGTH(cwt_filter_bq), cwt_filter_bq, st->cwt_filter[i].st);
+    /* debug */
+    /*
+    DEBUG_PRINTN("    avg: [");
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++)
+        DEBUG_PRINTN("%f, ", avg[i]);
+    DEBUG_PRINTN("]\n");
+    */
+    /* end */
+
+    float max_val = st->group.max;
+    int max_ch = st->group.max_ch;
+    int max_idx = st->group.max_idx + 1;
+    bool found = false;
+    if (debug) DEBUG_PRINTN("    rel: [");
+    for (size_t i=0; i<DSSS_GOLD_CODE_COUNT; i++) {
+        float val = cwt[i] / avg[i];
+        if (debug) DEBUG_PRINTN("%f, ", val);
+
+        if (fabs(val) > DSSS_THESHOLD_FACTOR)
+            found = true;
+
+        if (fabs(val) > fabs(max_val)) {
+            max_val = val;
+            max_ch = i;
+            max_idx = st->group.len;
+        }
+    }
+    if (debug) DEBUG_PRINTN("]\n");
+
+    /* debug */
+    if (debug) DEBUG_PRINT("    found=%d len=%d idx=%d ch=%d max=%f",
+            found, st->group.len, st->group.max_idx, st->group.max_ch, st->group.max);
+    /* end */
+
+    if (found) {
+        /* Continue ongoing group */
+        st->group.len++;
+        st->group.max = max_val;
+        st->group.max_ch = max_ch;
+        st->group.max_idx = max_idx;
+        return;
+    }
+    
+    if (st->group.len == 0)
+        /* We're between groups */
+        return;
+
+    /* A group ended. Process result. */
+    DEBUG_PRINT("GROUP FOUND: %8d len=%3d max=%f ch=%d offx=%d",
+            sim_pos, st->group.len, st->group.max, st->group.max_ch, st->group.max_idx);
+
+    /* reset grouping state */
+    st->group.len = 0;
+    st->group.max_idx = 0;
+    st->group.max_ch = 0;
+    st->group.max = 0.0f;
+}
+
+float run_iir(const float x, const int order, const struct iir_biquad q[order], struct iir_biquad_state st[order]) {
+    float intermediate = x;
+    for (int i=0; i<(order+1)/2; i++)
+        intermediate = run_biquad(intermediate, &q[i], &st[i]);
+    return intermediate;
+}
+
+float run_biquad(float x, const struct iir_biquad *const q, struct iir_biquad_state *const restrict st) {
+    /* direct form 2, see https://en.wikipedia.org/wiki/Digital_biquad_filter */
+    float intermediate = x + st->reg[0] * -q->a[0] + st->reg[1] * -q->a[1];
+    float out = intermediate * q->b[0] + st->reg[0] * q->b[1] + st->reg[1] * q->b[2];
+    st->reg[1] = st->reg[0];
+    st->reg[0] = intermediate;
+    return out;
+}
+
+float cwt_convolve_step(const float v[DSSS_WAVELET_LUT_SIZE], size_t offx) {
+    float sum = 0.0f;
+    for (ssize_t j=0; j<DSSS_WAVELET_LUT_SIZE; j++) {
+        /* Our wavelet is symmetric so convolution and correlation are identical. Use correlation here for ease of
+         * implementation */
+        sum += v[(offx + j) % DSSS_WAVELET_LUT_SIZE] * dsss_cwt_wavelet_table[j];
+        //DEBUG_PRINT("        j=%d v=%f w=%f", j, v[(offx + j) % DSSS_WAVELET_LUT_SIZE], dsss_cwt_wavelet_table[j]);
+    }
+    return sum / DSSS_WAVELET_LUT_SIZE;
+}
+
+/* Compute last element of correlation for input [a] and hard-coded gold sequences.
+ *
+ * This is intened to be used once for each new incoming sample in [a]. It expects [a] to be of length
+ * [dsss_correlation_length] and produces the one sample where both the reference sequence and the input fully overlap.
+ * This is equivalent to "valid" mode in numpy's terminology[0].
+ *
+ * [0] https://docs.scipy.org/doc/numpy/reference/generated/numpy.correlate.html
+ */
+float gold_correlate_step(const size_t ncode, const float a[DSSS_CORRELATION_LENGTH], size_t offx) {
+    float acc_outer = 0.0f;
+    uint8_t table_byte = 0;
+    for (size_t i=0, pos=0; i<DSSS_GOLD_CODE_LENGTH; i++, pos += DSSS_DECIMATION) {
+        float acc_inner = 0.0f;
+        for (size_t j=0; j<DSSS_DECIMATION; j++) {
+            if ((pos&7) == 0)
+                table_byte = dsss_gold_code_table[ncode][pos>>3]; /* Fetch sequence table item */
+            int bv = table_byte & (1<<(pos&7)); /* Extract bit */
+            bv = !!bv*2 - 1; /* Map 0, 1 -> -1, 1 */
+            acc_inner += a[(offx + i + j) % DSSS_CORRELATION_LENGTH] * bv; /* Multiply item */
+        }
+        acc_outer += acc_inner;
+    }
+    return acc_outer / DSSS_CORRELATION_LENGTH;
+}