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   acquisition · tracking · ranging · positioning

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Six end-to-end labs walking through the complete signal chain of a GNSS receiver — from Android raw measurements all the way to the correlation discriminators that lock onto a satellite signal. Each lab is a self-contained MATLAB implementation tackling a real engineering problem with real data.

Lab	Topic	Key Techniques
Lab 2	Multi-Constellation Positioning	LMS & WLMS, ECEF→LLA without toolboxes, KML export
Lab 3	Spreading Code Generation	GPS C/A PRN via 10-stage LFSR, Gold codes, GPS ICD validation
Lab 4	Signal Modulation & Spectrum	IF signal generation, BOC modulation, Welch PSD
Lab 5	GNSS Acquisition	CAF over real binary captures, FFT-accelerated CCCF, Doppler search
Lab 6	Code Tracking & Multipath	DLL discriminators, E-L / nE-nL / dot-product, multipath error envelope

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Lab Breakdown

Lab 2 — Multi-Constellation Least Squares Positioning

Both standard LMS and Weighted LMS positioning engines built from scratch, fusing GPS, GLONASS, Galileo, and BeiDou simultaneously. Processes multi-epoch datasets with realistic UERE noise models, computes positioning error statistics, and exports KML tracks for Google Earth visualization.

• ECEF-to-LLA conversion implemented without toolboxes (ecef2lla_noToolBox.m)
• Multi-GNSS geometry matrix construction with constellation-specific weighting
• Exported results: writeKML_GoogleEarth.m → viewable satellite track overlays

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Lab 3 — GPS & Galileo Spreading Code Generation

GPS C/A PRN code generator using a 10-stage linear feedback shift register — all 32 PRN codes validated against the official GPS ICD specification. Extended to Galileo E1b/E1c. Deep-dive into code properties: autocorrelation peaks, cross-correlation floors, balance/run-length statistics.

% Core PRN generator — Phase_Selector table maps PRN index to G2 tap pair
function Code = PRN_Generator(PRN_Code_Number)
  Phase_Selector = [2,6; 3,7; 4,8; ...];  % All 32 PRN tap assignments
  % 10-stage G1 + G2 LFSR — Gold code construction

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Lab 4 — Signal Generation & Spectral Analysis

Generates GPS and Galileo IF signals from scratch — complex carrier, spreading code upsampled at 16.368 MHz (generateLocalCode.m), and Binary Offset Carrier (BOC) modulation for Galileo (generateLocalIIF.m). Analyses resulting spectra using Welch's method and contrasts GPS BPSK vs. Galileo BOC(1,1) power spectral densities.

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Lab 5 — GNSS Signal Acquisition

Full Cross-Ambiguity Function (CAF) acquisition engine: 2D search over PRN code delay and Doppler frequency shift using FFT-accelerated cross-correlation. Doppler bins sweep ±5 kHz with spacing Δf = 2/(3·Tcoh) for guaranteed detection.

% FFT-based CCCF per Doppler bin — run over all 32 GPS PRNs + all Galileo codes
CCCF_GPS(i,:) = ifft(fft(localSignal) .* conj(fft(RawData)));
CCCF_GPS(i,:) = CCCF_GPS(i,:) / DelayBins;

Runs on three real binary GNSS captures (SignalRX_1/2/3.bin) — not just simulations. Peak detection in delay-Doppler space identifies visible satellites and extracts coarse Doppler estimates.

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Lab 6 — Code Tracking & Multipath Mitigation

Implements the Delay Lock Loop (DLL) discriminator core with Early, Prompt, and Late correlators. Three discriminators compared:

Discriminator	Formula	Property
Early-minus-Late (E-L)	R_E − R_L	Classic — simple, noise-sensitive
Normalized E-L (nE-L)	(R_E − R_L) / (R_E + R_L) × 0.5	Amplitude-normalized
Dot-Product	(R_E² − R_L²) / (R_E² + R_L²) × 0.5	Steeper slope, better sensitivity

Synthetic multipath scenario: 0.4× amplitude reflected ray at 0.25 chip delay, added via FlagMultipath flag. Multipath error envelopes characterised for each discriminator — showing quantitatively which ones degrade least under reflections.

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Tech Stack

Language       : MATLAB
GNSS Data      : Android GnssLogger exports, real binary IF captures
Constellations : GPS (L1 C/A), Galileo (E1b/E1c), GLONASS, BeiDou
Signal Freq    : 1575.42 MHz (L1), IF at 4.092 MHz, fs = 16.368 MHz
Chip Rate      : 1.023 Mchip/s (GPS C/A)

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Skills Demonstrated

• Full GNSS receiver chain: spreading codes → IF signals → CAF acquisition → DLL tracking
• Statistical estimation: LMS, WLMS, multi-epoch fusion without toolbox shortcuts
• DSP fundamentals: FFT-based correlation, Welch PSD, complex baseband, digital filtering
• Multi-constellation processing: heterogeneous satellite fusion with noise weighting
• Real-world signal handling: Android GnssLogger pipeline, binary IF capture processing

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M.Sc. Communications Engineering — Politecnico di Torino