RFanalyzer

A python tool for analyzing the impedance and return loss of an RF circuit

Installation

Firstly, clone to your machine.

git clone git@github.com:byggemandboesen/RFanalyzer.git

The library only relies on Numpy except if you will also be using the Touchstone class in which case you also need scikit-rf.

pip install scikit-rf

Example

The example below, shows the analysis of matching circuit for a 25Ohm antenna to a 50Ohm generator at 2.4GHz.
This is done using both series and parallel components to highlight the capabilities of the library.

import numpy as np

from RFanalyzer import Circuit, Stackup
from RFanalyzer.transmission_lines import Microstrip
from RFanalyzer.lumped_components import Resistor, Inductor, Capacitor
from RFanalyzer.loads import Load, Open, Short

# Define PCB stackup
su = Stackup(er=4.3, ur=1, h=0.5)
# Define microstrip width
ms_w = 1
# Define analysis frequency
f = np.arange(start=2, stop=2.8, step=0.02)*10**9

# Build circuit
components = [
    [Capacitor(capacitance=1*10**(-12))], # 1pF series capacitor
    [Microstrip(length=5, width=ms_w)], # 5mm series microstrip line
    [None, Inductor(inductance=5.5*10**(-9)), Short()], # 5.5nH parallel inductor to ground
    [Microstrip(length=10, width=ms_w)],
    [Load(25*np.ones_like(f, dtype=np.complex128))] # Antenna (assuming constant 25Ohm across frequency range)
]
circuit = Circuit(components=components, stackup=su)

# Compute circuit input impedance and return loss using a 50Ohm generator
Z_in = circuit.inputImpedance(f=f)
s11 = circuit.returnLoss(f=f, Z_source=Load(impedance=50))

Plotting these results yields the performance shown below.

The circuit above can be seen below using Smith V4.1.

TODO

• Automatically optimize matching component values
• Monte Carlo sensitivity analysis
• Add simple distributed elements