Merge pull request #5 from Wireless-Information-Networking/feat/python-src

Feat/python src

Author: nmb735

main.py

@@ -0,0 +1,67 @@
+# =================================================================================================================================== #
+# ----------------------------------------------------------- DESCRIPTION ----------------------------------------------------------- #
+# This script contains the functions for analyzing Angle of Arrival (AoA) measurements from RFID systems, using the classical         #
+# antenna-array method "Beamforming". It includes the classic delay-and-sum (DS) beamforming and the weighted DS beamforming, using   #
+# RSSI data for the weights.                                                                                                          #
+# =================================================================================================================================== #
+
+
+# =================================================================================================================================== #
+# --------------------------------------------------------- EXTERNAL IMPORTS -------------------------------------------------------- #
+import numpy as np  # Mathematical functions.                                                                                         #
+# =================================================================================================================================== #
+
+
+# =================================================================================================================================== #
+# ------------------------------------------------------- BEAMFORMING FUNCTION ------------------------------------------------------ #
+def beamforming_spectrum_calculation(phasor1, phasor2, rssi1, rssi2, L, wavelength, aoa_scan):
+    """
+    Calculate the beamforming spectrum (both standard and RSSI-weighted) for RFID AoA estimation.
+    
+    Parameters:
+        - phasor1    [np.ndarray] : Complex phasors from antenna 1
+        - phasor2    [np.ndarray] : Complex phasors from antenna 2
+        - rssi1      [np.ndarray] : RSSI values from antenna 1 (in dBm)
+        - rssi2      [np.ndarray] : RSSI values from antenna 2 (in dBm)
+        - L          [float]      : Antenna separation distance (in meters)
+        - wavelength [float]      : Signal wavelength (in meters)
+        - aoa_scan   [np.ndarray] : Array of angles to scan (in degrees)
+        
+    Returns:
+        - tuple        : (B_ds, B_w, theta_ds, theta_w)
+            - B_ds     : Standard delay-and-sum beamforming spectrum
+            - B_w      : RSSI-weighted beamforming spectrum
+            - theta_ds : Estimated angle using standard beamforming
+            - theta_w  : Estimated angle using RSSI-weighted beamforming
+    """
+    # STEP 1: Align phasors to the same length
+    N       = min(len(phasor1), len(phasor2))
+    phasor1 = phasor1[:N]
+    phasor2 = phasor2[:N]
+    # STEP 2: Transform RSSI from dBm to linear scale, and normalize by minimum value
+    all_rssi = [rssi1, rssi2]
+    rssi_min = min([np.min(r) for r in all_rssi])
+    w1       = np.sqrt(10**((rssi1 - rssi_min) / 10))  # Weight for antenna 1
+    w2       = np.sqrt(10**((rssi2 - rssi_min) / 10))  # Weight for antenna 2
+    # STEP 3: Calculate the beamforming spectrum
+    k    = 2 * np.pi / wavelength  # Wave number
+    M    = len(aoa_scan)
+    B_ds = np.zeros(M)  # Standard delay-and-sum spectrum
+    B_w  = np.zeros(M)   # RSSI-weighted spectrum
+    for m in range(M):
+        # Phase shift based on angle
+        dphi = k * L * np.sin(np.deg2rad(aoa_scan[m]))
+        # Standard delay-and-sum beamforming
+        y_ds    = phasor1 + np.exp(-1j * dphi) * phasor2
+        B_ds[m] = np.mean(np.abs(y_ds)**2)
+        # RSSI-weighted beamforming
+        y_w    = w1 * phasor1 + np.exp(-1j * dphi) * (w2 * phasor2)
+        B_w[m] = np.mean(np.abs(y_w)**2)
+    # STEP 4: Normalize spectra
+    B_ds = B_ds / np.max(B_ds) if np.max(B_ds) > 0 else B_ds
+    B_w  = B_w / np.max(B_w) if np.max(B_w) > 0 else B_w
+    # STEP 5: Find peak angles
+    theta_ds = aoa_scan[np.argmax(B_ds)]
+    theta_w  = aoa_scan[np.argmax(B_w)]
+    return B_ds, B_w, theta_ds, theta_w
+# =================================================================================================================================== #