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This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).

The Soil Moisture and Ocean Salinity (SMOS) mission is an Earth Explorer Opportunity mission from the European Space Agency (ESA). Its goal is to produce global maps of soil moisture and ocean salinity using the Microwave Imaging Radiometer by Aperture Synthesis (MIRAS). The purpose of the Passive Advanced Unit Synthetic Aperture (PAU-SA) instrument is to study and test some potential improvements that could eventually be implemented in future missions using interferometric radiometers such as the Geoestacionary Atmosferic Sounder (GAS), the Precipitation and All-weather Temperature and Humidity (PATH) and the Geostationary Interferometric Microwave Sounder (GIMS). Both MIRAS and PAU-SA are Y-shaped arrays with uniformly distributed antennas, but the receiver topology and the processing unit are quite different. The purpose of this work is to identify the elements in the MIRAS's design susceptible of improvement and apply them in the PAU-SA instrument demonstrator, to test them in view of these future interferometric radiometer missions.

Soil Moisture (SM) and Sea Surface Salinity (SSS) may seem to be unconnected, but both variables are intrinsically linked to the Earth's water cycle and the climate system. Thanks to the technological advances, the interest of the scientific community in remotely measuring SSS and SM has increased in the last years, spending much effort in this direction. The three current and planned Earth observation missions focused in these variables are: the MIRAS instrument aboard the SMOS mission of the European Space Agency (ESA) launched on November 2, 2009 [

an L-band radiometer to measure the brightness temperature,

a reflectometer to measure the sea state using reflected Global Positioning System (GPS) opportunity signals, sharing the Radio Frequency (RF) front-end, with the radiometer, and

an Infrared Radiometer (IR) to measure the physical surface temperature.

The PAU project is also a test-bed of new technological demonstrators such as real aperture radiometers with digital beamforming and polarization synthesis [

The fundamental operation of a synthetic aperture radiometer is the complex cross-correlation of the signals collected by each pair of channels (antenna + receiver), or baseline as shown in

The variables in _{Am}_{n} is the antenna temperature, _{m,n}_{m,n}_{m,n}_{B}_{RECm,n}_{mn}, v_{mn}_{n} − x_{m}, y_{n} − y_{m}_{0} that depends on the difference of the antenna positions normalized to the wavelength, being λ_{0} = _{0}. According to

Assuming that the collected signals are stationary random processes (thermal noise radiation) that fulfill the ergodicity property, narrow-band, spatially uncorrelated, and that the distance between antennas is much larger than the wavelength,

From the Van-Cittert Zernicke theorem [

𝛀_{m,n}

_{B} of_{p}_{q}

_{rec}

_{pq}_{pq}_{pq}

In addition,

A simplified version of

Assuming that all the antenna patterns are identical _{m}_{n}_{mn}

In these conditions, the modified brightness temperature can be recovered by means of the inverse Fourier transform of the visibility samples.

Each dual-polarization RF front-end is integrated behind a dual polarization patch antenna. The three main features of this receiver are: simultaneous dual polarization (V & H), frequency of operation (GPS L1 band) the same for both instruments (radiometer, and reflectometer), a three-stage down-converter, and a Local Oscillator (LO) inside each down-converter generated from a 10 MHz reference master clock common to all receivers. In this way, since the LO is generated inside each down-converter, their noises are uncorrelated from receiver to receiver and do not introduce a correlation offset. Each receiver translates the input signal from 1,575.42 MHz to an intermediate frequency of 4.309 MHz with a bandwidth of 2.2 MHz and an approximated gain of 110 dB. The differential Intermediate Frequency (IF) signal is sent to the Analog to Digital Converter (ADC) array unit through twisted pair (RJ45 grade 5) cables. These signals are digitalized at eight bits using IF sub-sampling techniques with a sample frequency of _{s}

The detailed description of the calibration approach is described in [

An overview of the PAU-SA instrument is first given in Section 3 to provide a global understanding of the system.

The first element of the instrument are the antennas. These are square patch antennas [_{𝛀} = 0.98, and half-power beam width of 60°. The antenna array consists of 25 antennas distributed over a Y-shaped array, with 8 antennas per arm, and a central one for radiometry applications. Three extra dummy antennas (with no receiver connected) are placed at the end of each arm to improve the antenna voltage patterns similarity as analyzed in [

The receiver has been designed to combine two different sub-systems: an L-band radiometer and a GNSS-Reflectometer. Since the reflectometer part requires continuous data acquisition, the input cannot be chopped. Therefore, Total Power Radiometer (TPR) topology for each vertical and horizontal polarization has been selected (

To improve the Alias-Free Field Of View (AF-FOV), the receiver has been implemented in reduced dimensions (11 cm × 7 cm × 3 cm). Taking into account that the operating frequency is the L1 GPS band, many already existing commercial off-the-shelf (COTS) components have been used for the implementation of this receiver, such as the Zarlink GP2015 GPS front-end as down-converter [

In order to ensure a constant impedance of the transmission lines, the RF stage has been implemented with ROGERS 4003 0.8 mm thickness substrate. Its structure consists of two parts, the switching stage and then an amplification stage. The main objective of the RF stage is to achieve a gain of at least 30 dB over the input signals, keeping the Noise Figure (NF) as low as possible. This is necessary to work in the linear region of the down-converter module located in the IF stage. The matching of each input/output ports have to be at least −22 dB. The required isolation between antenna signal and calibration (correlated and uncorrelated) signals has been experimentally determined to be better than −80 dB. Finally, the cross-talk between adjacent TPR have to be better than −40 dB.

The switching stage is controlled through CTR1 and CTR2 signals by the Control Unit (CU) implemented in the FPGA. It switches between three different states: the antenna measurements, calibration with external correlated signals (either noise or Pseudo-Random Noise (PRN) signal), or calibration with uncorrelated noise generated by an internal 50 𝛀 matched load. Usually this stage is connected to antenna acquisition, necessary for GNSS-R applications. The antenna input is connected directly to the patch antenna through a 50 𝛀 cable. Calibration with correlation signal is required to compensate different phases and amplitudes among channels. To implement this structure two switches model RSW-2-25P by MiniCircuits have been used, one for each radiometer, increasing the isolation between correlated noise and antenna signal. Once selected, the signal is amplified to adjust the antenna input power (∼−110 dBm) to the down-converter linear behavior power margin. The total RF gain is ∼33.3 dB, obtaining an input power level for down-converter of ∼−76.7 dBm, within the linear behaviour, and the total NF of 2.2 dB.

The main goal of the IF stage is to shift the RF signal to IF using a superheterodyne receiver or down-converter. Moreover this stage pre-amplifies the IF signal and transmits it to the ADC module through an Ethernet cable. This stage has been implemented with FR4 substrate. The output of each RF chain is interconnected by means of a semi-flexible cable to the input of each down-converter located in this stage. It mainly consists of the translation from 1,575.42 MHz to 4.309 MHz with a bandwidth of 2.2 MHz amplifying the RF signal by approximately 52 dB. The down-converter requires a 10 MHz Transistor–Transistor Logic (TTL) clock signal. This signal is distributed by a coaxial cable and it is used to internally synthesize the different LOs by means of the Phase Lock Loop (PLL)s. Usually these devices provide the output at IF, digitized at 2 bits (sign and magnitude) enough to recover the Coarse Acquisition (C/A) code, used in GPS applications. Originally, it was intended to determine the signal's power using just 1 bit as in [

At the receiver's output the signals are centered around _{IF}

The design of PAU-SA's receiver has been based on PAU-Real Aperture (PAU-RA) [

Once the RF and IF boards are assembled separately, they have been assembled and interconnected, as shown in

The sub-systems implemented in the FPGA are:

In-phase (I) and quadrature (Q) demodulation of the receivers' output digital signals coming from the array of 8 bits ADC),

Digital Low Pass Filter (LPF) at 8 bits,

Power estimation system of the 50 receivers' output signals (25 receivers × 2 polarizations @ 8 bits).

Correlation unit of the three correlation matrices (V, H, VH) @ 1 bit, and

Communication protocol and control with a PC, and data collection.

The FPGA device used in the design is the Xilinx Virtex-4 LX 60 distributed. _{rms}

The fundamental requirement of a sequential electronic block is the frequency of operation. In the case of the ADC, the frequency of operation determines the sampling frequency. In the PAU radiometer the receiver has a 4.309 MHz intermediate frequency, and then it is digitized to translate the frequency to baseband with the Digital Down Converter (DDC). The Nyquist sampling theorem states that the sampling frequency should be at least twice the highest frequency components in the signal. This means that to sample a 4.309 MHz signal, a minimum 8.618 MHz sampling frequency is required. A higher sampling frequency implies a higher data rate, and the DDC function will be more complex to implement in the FPGA because the input signal of DDC should be multiplied by a cosine function using all the 8 bits. Another option is the so called “band-pass sampling”. With this technique a smaller sampling frequency can be used, thus reducing the data rate, while simplifying the implementation of the DDC. The “band-pass sampling” technique is described in the following paragraphs. If the input signal of DDC is multiplied by cos(𝛀_{digital}_{digital}

This means that now, the input signal has to be multiplied by 1,0,-1,0 thus simplifying the numerical computation. Now, it is possible to compute the sample frequency of the ADC, considering the sampling frequency of ADC (_{S}_{IF}

Taking _{FINAL}_{S}_{S}

Thus, the output signal of the ADC is centered at the frequency _{FINAL}

Before calculating the correlation matrices, it is necessary to down-convert the digital signals of the receivers to baseband and obtain their in-phase (I) and quadrature (Q) components. This section briefly presents the theoretical formulation and then explains the main blocks. The I/Q demodulation unit is composed of four blocks as shown in

Once the receiver's signal has been digitized the output has the following expression:
_{digital}

Taking into a count the previous equation, it is possible to obtain the

If these expressions are particularized to the digital frequency (_{digital}

Working with the ADCs and using band-pass sampling, it is then possible to work with a specific digital frequency that minimizes the required hardware resources. In this particular case it is not necessary to implement a multiplier stage, but only to take a sample out of two with the corresponding sign. These modules are implemented with a multiplexer block and an inverter function. In

To recover the normalized visibility function as derived from the correlation matrix (

Since our signal is thermal noise, the power measurement can be obtained either from the IF signal or from each of the I/Q components. For the sake of simplicity, the I and Q components have been used. To implement a power measurement system a multiplier and an adder are required. For this application the internally implemented FPGA functions are used.

The computation of the digital correlations and the power measurements are the two pre-processing steps implemented in the FPGA. The Digital Correlation Unit DCU measures the similarity between both signals using 1 bit (sign bit). It basically consists of counting the number of samples (_{c}_{cmax}_{S}_{int}_{cmax}^{23} ≃ 8.388 MS counter enough to count up to 5.745 MSamples. In this case, with 25 receivers and the _{r}_{i}

To implement only one polarization matrix, 676 results of 23 bits are necessary. Due to limitations in the FPGA resources the internal Random Access Memory (RAM) memory has been used to implement the counters (676 × 3 = 2,026 counters). Also, since the frequency of operation is higher than the sampling frequency (_{CLK}_{S}

This value means that it is possible to do 18 internal operations until the next sample arrive. In our case the FPGA used has 160 independent RAM blocks to implement 3 correlation matrices, this means 53 blocks for each block. In this case, the required hardware reuse factor is:

The Classical noise source has been implemented with a NoiseCom noise source model NC346D with an Excess Noise Ratio (ENR) of 21.31 dB [_{n}_{0} is the reference temperature (290 K). In this case, the resulting _{n}

Pseudo-Random Noise (PRN) sequences are signals with very long repetition periods that are used in a variety of applications, such as Code Division Multiple Access (CDMA) communications or positioning systems. They have a relatively flat spectrum over a bandwidth determined by the length of the sequence and the speed of the code or Symbol Rate (SR). Their spectra look like the noise spectrum, and the calibration of a microwave correlation radiometer (either interferometric or polarimetric) can benefit from these properties The SR parameter is used to determine the speed of the PRN code in order to control the bandwidth of the spectrum. The symbol rate is defined as the ratio of the bandwidth of the PRN signal (_{PRN}_{PRN}_{PRN}_{chips}

The equivalent noise temperature of the PRN signal (_{PRN}_{PRN}^{2}/2 ≜ _{B}_{PRN}_{PRN}_{PRN}_{B}

The PRN is generated with a Linear Feedback Shift Register (LFSR) [

The system has been designed to have the possibility to select between 10 or 20 order primitive polynomials which maximum-length to generate two pseudo-random sequences of length 2^{nbits} −

Once the two different noise sources (thermal and PRN) have been independently generated, these are injected into a selector circuitry (

In order to minimize the area these modules have been integrated in different layers. In the bottom layer the Noise Source module and the selection circuitry have been implemented and the PRN sequences module in the top layer. The FPGA 2 synthesizes the PRN sequences. It is controlled with a DB15 connector through the internal PC as shown in

Before starting with the design of the mobile unit it has been necessary to define a set of specifications in order to establish the necessary requirements to transport the PAU-SA and the Multi-frequency Experimental Radiometer With Interference Tracking For Experiments Over Land And Littoral (MERITXELL) [

The Digital Correlation Unit (DCU) computes all possible cross-correlations between antenna pairs at each polarization by counting the number of samples with the same sign (1 bit), obtaining the so-called correlation counts matrices (_{cm,n}_{cmax}_{cm,n}_{cm,n}_{cmax}_{S}_{int}_{cmax}

Finally, these matrices, and the power measurements are sent to an external PC in real time, where the calibration and the image reconstruction algorithms are implemented to retrieve the brightness temperature image.

The first step consists of computing the cross-correlation (̿) by normalizing the correlation count matrix _{cm,n}_{cmax}

The digital correlation (_{m,n}_{m,n}_{m,n}_{m,n}

The normalized cross-correlation (

However, this relationship is only valid for ADCs having a zero offset (ideal case). Taking into account the sample threshold error, to correct the correlation offset, the normalized correlation ^{−6}.

In _{01} is calculated in the last column of the matrix of correlators (26^{th} column) as the cross-correlator between the in-phase components (_{01} is computed in the last row (26^{th} row) as the cross-correlator between the quadrature components (

_{m,n}_{ph}

Once the normalized complex cross-correlations _{m,n}

Finally, the visibility samples must be corrected for phase and amplitude errors [

Since the I/Q demodulation is performed digitally, quadrature errors are zero and do not have to corrected.

System temperatures are measured with digital PMS, therefore they are insensitive to offset and slope drifts as opposed to their analog counter parts,

Visibility offsets are measured with an internal matched load and by looking to an external absorber, and

Phase and amplitudes of the visibility samples are measured using either a centralized noise source or a pseudo-random noise sequence PRN [

Afterwards, these visibility samples must be re-ordered and assigned to the corresponding baseline ((

One of the main differences between MIRAS and PAU-SA is the frequency of operation. L-band radiometer should operate in the 1,400–1,427 MHz “protected” band as MIRAS. However, PAU-SA is an instrument concept demonstrator, and to minimize the hardware requirements the GPS reflectometer and the L-band radiometer share the same front-end and frequency band. Although sharing the same front-end provides a significant hardware reduction, there are some drawbacks. The first one concerns to the possible interference that GPS signals can introduce in the radiometric measurements. This non-optimal operation frequency for the radiometer instrument has an impact on the radiometric measurements, introducing some errors. This issue is analyzed in Section 5.1. The second one concerns the bandwidth. In the case of MIRAS, the bandwidth is limited by the protected band with a maximum value of 27 MHz, and an effective noise bandwidth of ∼19 MHz. For the PAU-SA instrument the bandwidth is 2.2 MHz imposed by the IF frequency of the GP2015 chip from Zarlink being used, and by the SAW filters used for the implementation of the receiver chain. This reduction in the bandwidth has an impact on the radiometric sensitivity that can only be compensated by increasing the integration time, which is not critical in a ground-based instrument.

Each arm of the MIRAS instrument is approximately three times longer than the PAU-SA ones: ∼4 m with 23 elements in front of 1.3 m with just 8 elements. The total number of antennas in MIRAS is 69 and 25 in the case of PAU-SA. This decision was taken for two reasons: the first one is due to the use of fixed non-foldable arms in order to simplify the mechanical complexity, and the second one was pragmatic: to be able to take the instrument out of the laboratory, where it was assembled. Since the bandwidth of PAU-SA is narrower than that used in MIRAS and the arm length is smaller, spatial decorrelation effects modeled by the FWF are negligible. This factor is quantified in Section 5.2. One of the improvements of PAU-SA is the additional dummy antenna at the end of each arm to improve the antenna pattern similarity (

Concerning the antenna type and separation, they are quite similar in both instruments. For instance, both MIRAS and PAU-SA use patch antennas without dielectric substrate for the V- and H-polarizations. For hardware simplicity, MIRAS has sequential acquisitions since the receiver is shared for both polarizations. In the case of PAU-SA, each polarization has its own receiver channel. Therefore, continuous acquisitions at both polarizations can be obtained simultaneously, as well as mixing the polarizations.

In order to increase the AF-FOV, the minimum distance between element spacing is kept to the minimum, only limited by the receiver's size. MIRAS has an antenna spacing of 18.75 cm, corresponding to 0.875 λ at 1,400 MHz. In the case of PAU-SA the antenna spacing is reduced to 15.5 cm = 0.816 λ at 1,575.42 MHz, the GPS L1 signal.

Moreover, the distribution of the LO used in the down-converter is different in both instruments. In MIRAS the LO is fed to groups of 6 elements forming an arm section, whereas PAU-SA uses a centralized reference clock of 10 MHz, and the LO is generated by means of a PLL inside each receiver to minimize offsets coming from common LO noise leaking through the mixer.

MIRAS'quantification scheme uses 1 bit sampling at intermediate frequency IF [

Due to the large number of receivers in interferometric radiometers, it is advisable to obtain a quasiperfect matching of the frequency responses, mass reduction, and to eliminate temperature and frequency drifts as much as possible. For these reasons, the most important contributions in PAU-SA are focused on the replacement of analog by digital subsystems being the most important:

I/Q down-conversion to eliminate quadrature errors,

Digital filtering, replacing the narrow RF filter by a digital IF filter, to obtain a mass reduction, a quasi perfect matching, and eliminating thermal and frequency drifts, and

Digital Power estimation, eliminating the classical Schottky or tunnel diodes to achieve a mass reduction, and eliminating temperature drifts and aging.

All these subsystems and the DCU that computes the full cross-correlation matrix (V, H and V/H) have been implemented in a Virtex 4 FPGA. In this case, since the clock frequency is much higher than the sampling frequency, hardware reuse techniques are used to compute the full-polarization matrices in each snapshot.

The imaging capabilities can be sequential dual-polarization or full-polarimetric in MIRAS, and non-sequential full-polarimetric in PAU-SA. The use of both polarizations simultaneously is also necessary to compose the reflected LHCP GPS signal.

The integration time is fixed for MIRAS with a value of 1.2 s, while PAU-SA has predefined 4 values: 10 ms, 100 ms, 0.5 s and 1 s for test purposes.

Finally, MIRAS uses a classical correlated noise injection method for calibration proposes. Due to the large number of receivers to feed, it is necessary to use several noise sources distributed along the instrument increasing the hardware complexity, and introducing additional noise. In addition, the distributed noise injection is not capable of calibrating all sorts of errors. To overcome this problem PRN signals can be used instead of a centralized noise source for calibration purposes. Moreover, since the PRN signals are deterministic and known, new calibration approaches are feasible through the correlation of the output signals with a local replica of the PRN signal, leading to the estimation of the receivers' frequency responses and the FWF [

The receiver's operating frequency is defined by the L1 signal of the GPS signal (1,575.42 MHz), which is also suitable for SSS estimation. On one hand the GNSS signals use spread spectrum techniques. After the scattering on the sea surface, the power of these signal is at least 23 dB below the thermal noise. For this reason, and thanks to the 30.1 dB correlation gain, GNSS-Reflectrometry can detect the GPS signal when the correct C/A code is applied. On the other hand, from the radiometer point of view, the noise signal to be detected is at least 23 dB above the GPS signal so the radiometric error induced is minimum, and it only occurs in the directions of specular reflection which are known a prior. Therefore, it is possible that both the radiometer and the reflectometer share the same receiver. Although the spread-spectrum of the GPS modulation is at least 23 dB below the noise level (PAU-SA as a radiometer), its impact has to be quantified specially since the synthesized beam is very narrow. The GPS signal includes the P, C/A and M codes.

The first one is the P code, having the largest repetition period of 6.1871 × 10^{12} bits long (6,187,100,000,000 bits, ∼773.39 gigabytes) repeating once a week, and achieving a ∼75 dB compression gain with a 22 MHz band, and the received power level is ∼−133 dBm (−143 dBm in the ∼2.2 MHz C/A code bandwidth) [

The Fringe-Wash Function FWF accounts for the spatial decorrelation of the signals coming from a given direction at a given baseline. Precisely, the FWF is related to the frequency responses of the receivers forming the baseline.

The amplitude of the FWF can be modeled around the origin by means of a sine function as:

The maximum value is found for the largest baseline Δ_{max}_{max}

The maximum antenna separation is given by:
_{EL}_{EL}_{max}

This section is divided into three parts. The first part presents the temperature characterization of the instrument, the second part is the characterization at baseline level in an anechoic chamber, and the last part is an outdoor experiment with the instrument.

Since receivers exhibit phase and amplitude drifts due to temperature changes, it is necessary to stabilize and control the temperature of the instrument. The better the temperature control, the longer the inter-calibration period will be. The PAU-SA's stability temperature is controlled by Proportional Integral Derivative (PID) devices located in each arm, and in the central part or hub. Moreover, it has an air control by means of fans to distribute the air along the instrument and forcing the air circulation as much as possible, but in the case of the HUB it is not sufficient, being the warmest the central elements.

The tests performed at baseline level are: the characterization of the radiometer noise and its stability through the “Allan's variance” [

In order to determine the optimum range of integration times for best use of the system, the characterization of the radiometer noise and stability has been performed measuring the Allan's variance [_{n}^{th}

It shows the evolution of the variance of both channels

However, due to system instabilities, after a given value of

The characterization of the radiometric resolution has been performed with the set up shown in

Concerning the shape of the circle is clearly distinguished up to 2 × 20 dB attenuators, and since the I/Q demodulation is performed digitally, there are neither quadrature errors, nor amplitude unbalances between branches that need to be corrected [_{c}_{SYS}_{SYS}_{ph}_{c}_{ph}_{REC}_{SYS}^{−3}, which is very close to the measured value (

Moreover other tests have been performed in the anechoic chamber [

In this situation, the theoretical real and imaginary normalized correlations should vary according to: real part in

Due to the previous considerations, in

This section summarizes a couple of experimental results carried out with the PAU-SA instrument, calibration procedures and extended results are presented in detail in [

The second test has been the determination of the angular resolution transmitting two point sources to the instrument and using a hexagonal inverse Fourier transform, and a rectangular window with an angular resolution of Δ

The radiometric resolution is the standard deviation of the time fluctuation of a given observable. It is the minimum change detectable by the instrument and it is computed as in _{v,h}

The radiometric precision is the systematic error in each pixel. An average radiometric precision value is computed for the whole alias-free field-of-view image as the RMS value of the brightness temperature computed from the average of 80 snapshots of 3 s integration time each (total 240 s), so as to achieve a negligible radiometric resolution). It is estimated by using _{v}_{h}

The radiometric bias is the spatial mean of the computed brightness temperature minus a reference temperature determined by

Finally, since the instrument was conceived as a technology demonstrator, commercial GPS chips operating at L1 band were used, making it possible to track the GPS constellation.

This paper has described the PAU-SA instrument. It is a synthetic aperture radiometer that has been designed and tested to study potential improvements in SMOS follow-on or in other missions using synthetic aperture radiometers as GAS [

This work, conducted as part of a EURYI (European Young Investigator) Award, 2004, was supported by funds from the Participating Organizations of EURYI and the Spanish Ministry of Science and Innovation and AYA2011-29183-C02-01.

Sketch of the fundamental operation of an interferometer: each pair of receiving channels and a complex correlator form a baseline that measures a sample of the visibility function from [

Picture of PAU-SA's array without radome from [

Global view of the PAU-SA's architecture from [

PAU-SA's system block diagram indicating the interface connections between different modules from [

PAU-SA's receiver block diagram uses two TPR topologies, one per polarization (V & H) from [

(

Overview of the sub-systems implemented in the FPGA (radiometer part) and peripherals in PAU-SA from [

(

Block I/Q demodulation unit from [

(

PAU-SA's correlation counts matrix _{cm,n}

Elemental correlator block (from [

Correlated noise unit block diagram from [

PRN generator module circuitry from [

Spectrum analyzer acquisitions of different PRNs generated with different SRs. Central frequency of 1,575.42 MHz, 2 MHz/div, span = 20 MHz and 10 dB/div. (

Hardware implementation of the selection circuitry from [

Hardware implementation of the correlated noise unit from [

(_{B}_{B}

(

Sample time evolution of the PAU-SA's receivers acquired during the day (2011-02-15) from [

(

(

(

Measurement setup using a PRN signal as point sources at 10 m of the instrument. (

(

Comparative between MIRAS and PAU-SA. Table from [

1 | Altitude | Global observation, Low Earth Orbit (LEO): orbital altitude of 763 km, 3 days equatorial revisit time | On-ground | |

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2 | Frequency operation | L-band (1,400–1,427 MHz) band is protected for passive observations | L1-band (1,575.42 MHz) GPS signal | Same frequency for Radiometer and GNSS-Reflectrometer |

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3 | Bandwidth | 19 MHz | 2.2 MHz | Negligible spatial correlation effects |

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4 | Number of antennas per arm | 4 m | 1.3 m | |

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5 | Number total antennas | 69 | 31 | 8 × 3 + 1 = 25 for Radiometer, 3 center plus 3 additional = 7 antennas for GNSS-Reflectometer, 3dummy antennas, 1 at the end of each arm |

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7 | Antenna type | Patch antenna without dielectric substrate and V & H polarizations (non-simultaneous) | Patch antenna without dielectric substrate and V & H polarizations (simultaneous) | Full-polarimetric (non-sequential) |

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8 | Antenna spacing | 0.875λ at 1,400 MHz, 21 cm wavelength | 0.816λ at 1,575.42 MHz, 19 cm wavelength | Increase the alias-free field of view |

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9 | Receiver type | 1 per element | 1 per polarization (2 per element) | Full-polarimetric possible (non-sequential) |

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10 | Topology of the LO down-converter | Distributed local oscillator (LO) (groups of 6 elements) | Centralized reference clock + Internal LO generator | Elimination of correlation offsets due to LO noise leakage. |

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11 | Quantization | 1 bit IF sampling depending upon the noise uptake level (Inside the LICEF) | 8 bit IF sub-sampling using an external ADC | (8 bits) for I/Q conversion and (1 bit) to power measurement |

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12 | I/Q down-conversion | Analog | Digital | Mass reduction, no quadrature errors (calibration not required) |

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13 | Frequency response shaped by | Analog RF filter | Digital low- pass filter | Mass reduction, quasi perfect matching, no temperature and frequency drifts |

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14 | Power measurement system (PMS) | Analog (diode detector) | Multibit Digital (FPGA) Computation | Mass reduction, no temperature drifts |

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15 | Digital Correlated Unit | _{CLK}_{s} |
_{CLK}_{s} |
Clock frequency (_{CLK}_{s} |

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16 | Image capabilities | Dual-polarization or full-polarimetric (sequential) | Full-polarimetric (non-sequential) | Necessary for GNSS-R applications |

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17 | Integration time | 1.2 s | Variable: 4 values 1 s, 0.5 s, 100 ms, 10 ms | |

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18 | Correlated Noise Injection | Distributed (Noise Source) | Centralized (Noise Source, or PRNs) | Using PRNs independent number of receivers (simpler and more flexible calibration) |