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A VNA is an instrument used to measure and analyze radio frequency circuits. It is important not to confuse it with a network analyzer, referring to computer network analyzers. When network analyzers were invented, computer networks did not exist, so the name is not more specific. computer networks did not exist, so the name is not more specific. Vector network analyzers are used to measure all kinds of devices, from filters and devices, from simple filters to complex modules used in satellite communications, depending on the satellite communications, depending on the characteristics of the device, it can test active devices (they generate an excitation). Test active devices (they generate an electrical excitation, gain, or control) or passive devices (they interconnect the different passive (interconnecting the various active components ensuring the transmission of the electrical signal or modifying its level). The electrical signal or modifying its level). They also measure devices with different linear as well as nonlinear behavior. For this, it can use frequency sweep and time sweep techniques.
Operation of a VNA
The vector network analyzer (VNA) measures the dispersion parameters of high-frequency circuits. When the frequency is sufficiently high, wave reflections become important, and distributed effects must be considered. The VNA can analyze circuits' reflection and transmission coefficients at high frequencies. The principle of operation is simple, VNA consists of a signal source that is used to excite the device under test (DUT), two directional couplers per port that measure transmitted and reflected waves, and detectors at the end of the couplers that can measure amplitude and phase of the signals. The signal source generates a test signal routed to one of the ports. The directional coupler of the receiver couples this signal, and its phase and amplitude are measured. phase and amplitude are measured. The rest of the signal exits the VNA port and enters the device under test. Part of the signal is reflected in the source port and measured by another directional coupler. The ratio of reflected power to transmitted power is used to calculate the reflection coefficient of the DUT. There is a difference between the wavelengths of the transmission lines within the VNA and the cables connecting the DUT. the cables connecting the DUT cause loss and affect the measured phase because the source and the source and load will not be perfect and will also reflect some return signal. There are also reflections from the internal components of the VNA. All errors also have some frequency dependence. The non-reflected part of the signal passes through the DUT, which can be attenuated or amplified after passing through the device. When the test signal exits the DUT, the signal is coupled by the directional coupler at the second port, and its phase and amplitude are measured. The rest of the signal passes to the termination, where it is absorbed. The transmission coefficient is calculated as the ratio of the received power to the transmitter power. When the measurement is repeated with the source switch connected differently, the DUT's reflection and transmission coefficients can be measured from the other direction.
Measurement of S-parameters
When measuring the S-parameters of an active circuit, you must include all the bias components as part of the two-port circuit and polarization components as part of the two-port circuits. The input frequencies need to be in the linear region of the circuit. Two 50-ohm loads will be needed to act as terminators. For active circuits, they will need to be used to couple large dc blocking resistors to termination resistors. The generator frequency is set to the desired frequency. Then, the source voltage and Vm1 and Vm2 are measured for both configurations. The phase measurement is the most difficult to perform since it is difficult to see the small phase differences in a field.
For the measurement, it is assumed that the source voltages have zero phases. It is necessary to measure the phase relative to the measured signal. If the phase of the measured signal delays (is to the right), then the phase must be negative. Voltage division is simple since the phase of the divider is zero. You only have to divide magnitudes. To subtract one, it is necessary to convert to rectangular coordinates S11 and S22 must always be less than 1 in magnitude, and for active circuits, S12 and S21 can be greater than 1.
The equations that relate the parameter to the measured voltage
We propose a method for 3D video at ~8 frames per second with 32 × 32 pixels resolution to be applied in hyperspectral camera single-pixel and RADAR for operating in outdoor applications with severe weather conditions or GPS-denied environments. Dynamic environments present different factors that limit performance in the quality image and video of conventional cameras based on RGB sensors as atmospheric effects, background light noise saturation, low-visibility, or obstacle on the scene, for which have been proposed different solutions from the integration of sensors hyper-spectral and fusion technologies as RADAR, and LIDAR. A low-cost solution for image sensors in low-light scattering media that offer more integration capacity with other sensors is a vision system based on the principle of single-pixel imaging (SPI). For that, we developed an SPI camera with active NIR illumination at wavelength 1550 nm in combination with millimeter RADAR in band 80 GHz for the generation of 3D video. For generation 3D video, we will implement an architecture GPU and define a reconstruction parallelized robust 3D algorithm based on the Shape-for-Shading (SFS) method, deep learning, and depth mapping with depth with RADAR to reach a near-continuous real-time 3D frame. As an experimental setup, we build a scenario to simulate different conditions environment as low-illumination, scattering, and irregularity surfaces, where we can evaluate the performance of our system vision in comparison with RGB camera using figure-of-merit as PSNR, RMSE, and VIF. Furthermore, to determine the system's capacity for future sensor vision by UAVs.
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