Retrieval improvements for the ALADIN Airborne Demonstrator in support of the Aeolus wind product validation

The realization of the European Space Agency’s Aeolus mission was supported by the long-standing development and field deployment of the ALADIN Airborne Demonstrator (A2D) which, since the launch of the Aeolus satellite in 2018, has been serving as a key instrument for the validation of the Atmospheric LAser Doppler INstrument (ALADIN), the first-ever Doppler wind lidar (DWL) in space. However, the validation capabilities of the A2D are compromised by deficiencies of the dual-channel receiver which, like its spaceborne counterpart, consists of a Rayleigh and a complementary Mie spectrometer for sensing the wind speed from both molecular and particulate backscatter signals, respectively. Whereas the accuracy and precision of the Rayleigh channel is limited by the spectrometer’s high alignment sensitivity, especially in the near field of the instrument, large systematic Mie wind errors are caused by aberrations of the interferometer in combination with the temporal overlap of adjacent range gates during signal readout. The two error sources are mitigated by modifications of the A2D wind retrieval algorithm. A novel quality control scheme was implemented which ensures that only backscatter return signals within a small angular range are further processed. Moreover, Mie wind results with large bias of opposing sign in adjacent range bins are vertically averaged. The resulting improvement of the A2D performance was evaluated in the context of two Aeolus airborne validation campaigns that were conducted between May and September 2019. Comparison of the A2D wind data against a high-accuracy, coherent Doppler wind lidar that was deployed in parallel on-board the same aircraft shows that the retrieval refinements considerably decrease the random errors of the A2D line-of-sight (LOS) Rayleigh and Mie winds from about 2.0 m∙s−1 to about 1.5 m∙s−1, demonstrating the capability of such a direct detection DWL. Moreover, the measurement range of the Rayleigh channel could be largely extended by up to 2 km in the instrument’s near field close to the aircraft. The Rayleigh and Mie systematic errors are below 0.5 m∙s−1 (LOS), hence allowing for an accurate assessment of the Aeolus wind errors during the September campaign. The latter revealed different biases of the L2B Rayleigh-clear and Mie-cloudy horizontal LOS (HLOS) for ascending and descending orbits as well as random errors of about 3 m∙s−1 (HLOS) for the Mie and close to 6 m∙s−1 (HLOS) for the Rayleigh winds, respectively. In addition to the Aeolus error evaluation, the present study discusses the applicability of the developed A2D algorithm modifications to the Aeolus processor, thereby offering prospects for improving the Aeolus wind data quality.

Performance Analysis of Spectrally Efficient Adaptive Spatial Modulation in MIMO System by using QAM

In this article, we proposed a multiple input multiple outputs (MIMO) technique such as spectrally efficient adaptive quadrature spatial modulation (SEAQSM) which is based on space modulation techniques (SMTs). SMTs are logarithmically proportional to transmitting antenna & this technique fulfills the requirement of high data rate in the MIMO system. The Spatial position of the transmitting antenna improves the performance of the MIMO system. In space modulation technique spectral efficiency is logarithmically proportional to transmit antenna, if we increase the antenna at the transmitter end then the bandwidth efficiency significantly improved. We have to improve the performance MIMO system, minimize the latency and low power consumption. The proposed technique performance is explored over Rayleigh fading channel for a particular MIMO. These techniques underestimate the transmit antennas with less RF chain. In this paper, we analyzed the performance of our proposed scheme with conventional SM and QSM by using MONTE CARLO Simulation in term of BER with distinct order of QAM symbol. SE acquired for varying SNR at a BER of 10−3are obtained for uncorrelated Rayleigh channel. Keywords: Spatial Modulation(SM), MIMO, Spectral efficiency, Energy efficiency, Quadrature Spatial Modulation (QAM), Maximum Likelihood (ML) detector.

A Low-Complexity Demodulation for Oversampled LoRa Signal

This paper deals with a method of demodulation for oversampled LoRa signal. The usual maximum likelihood (ML) based demodulation method for LoRa chirp spread spectrum (CSS) waveform is dedicated to signals sampled at Nyquist rate, whereas considering oversampled signals may improve the performance of the LoRa demodulation process. In this respect, when an oversampling rate (OSR) 2 is assumed, the method suggested in this paper consists in applying two demodulation processes to the even and odd samples of the oversampled LoRa signal, and then combining the results. This principle is then generalized to any OSR, and we show that the complexity of the method is low since it only involves discrete Fourier transforms (DFT). Moreover, a performance analysis in terms of symbol and bit error rate (SER and BER) is presented considering both additive white Gaussian noise (AWGN) and Rayleigh channel models. Simulations show the relevance of the method and the performance analysis as a gain of 3 dB is achieved by the demodulation at OSR 2 compared with OSR 1.

A Low-Complexity Demodulation for Oversampled LoRa Signal

This paper deals with a method of demodulation for oversampled LoRa signal. The usual maximum likelihood (ML) based demodulation method for LoRa chirp spread spectrum (CSS) waveform is dedicated to signals sampled at Nyquist rate, whereas considering oversampled signals may improve the performance of the LoRa demodulation process. In this respect, when an oversampling rate (OSR) 2 is assumed, the method suggested in this paper consists in applying two demodulation processes to the even and odd samples of the oversampled LoRa signal, and then combining the results. This principle is then generalized to any OSR, and we show that the complexity of the method is low since it only involves discrete Fourier transforms (DFT). Moreover, a performance analysis in terms of symbol and bit error rate (SER and BER) is presented considering both additive white Gaussian noise (AWGN) and Rayleigh channel models. Simulations show the relevance of the method and the performance analysis as a gain of 3 dB is achieved by the demodulation at OSR 2 compared with OSR 1.

Relationship between wind observation accuracy and the ascending node of the sun-synchronous orbit for the Aeolus-type spaceborne Doppler wind lidar

The launch and operation of the first spaceborne Doppler wind lidar (DWL), Aeolus, is of great significance for observing the global wind field. Aeolus operates on a sun-synchronous dawn–dusk orbit to minimize the negative impact of solar background radiation (SBR) on wind observation accuracy. Future spaceborne DWLs may not operate on sun-synchronous dawn–dusk orbits due to their observational purposes. The impact of the local time of ascending node (LTAN) crossing of sun-synchronous orbits on the wind observation accuracy was studied in this paper by proposing two given Aeolus-type spaceborne DWLs operating on the sun-synchronous orbits with LTANs of 15:00 and 12:00 LT. On these two new orbits, the increments of the averaged SBR received by the new spaceborne DWLs range from 39 to 56 mW m−2 sr−1 nm−1 under cloud-free skies near the summer and winter solstices, which will lead to uncertainties of 0.19 and 0.27 m s−1 in the increment of the averaged Rayleigh channel wind observations for 15:00 and 12:00 LT orbits using the instrument parameters of Aeolus with 30 measurements per observation and 20 laser pulses per measurement. This demonstrates that Aeolus operating on the sun-synchronous dawn–dusk orbit is the optimal observation scenario, and the random error caused by the SBR will be larger on other sun-synchronous orbits. Increasing the laser pulse energy of the new spaceborne DWLs is used to lower the wind observation uncertainties, and a method to quantitatively design the laser pulse energy according to the specific accuracy requirements is proposed in this study based on the relationship between the signal-to-noise ratio and the uncertainty of the response function of the Rayleigh channel. The laser pulse energies of the two new spaceborne DWLs should be set to 70 mJ based on the statistical results obtained using the method. The other instrument parameters should be the same as those of Aeolus. Based on the proposed parameters, the accuracies of about 77.19 % and 74.71 % of the bins of the two new spaceborne DWLs would meet the accuracy requirements of the European Space Agency (ESA) for Aeolus. These values are very close to the 76.46 % accuracy of an Aeolus-type spaceborne DWL when it is free of the impact of the SBR. Moreover, the averaged uncertainties of the two new spaceborne DWLs are 2.62 and 2.69 m s−1, which perform better than that of Aeolus (2.77 m s−1).

Studying and Modeling the Performance of the TCM-STBC Systems in the Rayleigh Channel

Multiple-input multiple-output (MIMO) systems will play an important role in future generations of wireless networks. Space-time block code (STBC) and space-time trellis code (STTC) are two techniques that may be used in multi-antenna radio systems. This paper aims, most importantly, to study the performance of STBC systems at different vallues of such parameters as spectral efficiency, matrix codes and constellations. A performance comparison between STBC and STTC schemes is performed. In order to show the efficiency of the system’s ability to communicate with uncoded and coded transmission structures over AWGN and Rayleigh channels, the trellis-coded modulation (TCM) is introduced. The results obtained show that the proposed TCM-STBC system model, using one and two receiving antennas, improves the performance of Rayleigh channel communication systems at 9.5 dB and 11.5 dB for a BER of 10−5

Aeolus aerosol and cloud product

<p>The European Satellite has the first space-borne high-spectral resolution UV lidar onboard called ALADIN. Two detection channels, a broadband (Rayleigh channel) and a narrowband (Mie channel), are implemented. Carefully calibrated, this combination offers the possibility to derive independent estimates of the backscatter and extinction coefficients of clouds andaerosols, leading to a direct estimation of the lidar ratio, useful for aerosol classification.</p><p>The presentation will show how the official processor of the mission works for the retrieval of optical properties of cloud and aerosol particles, with a focus on the currently available products (called L2A). The potential of the L2A processor will be illustrated by results obtained on data acquired since Aeolus launch and by comparisons to ground based lidars in the frame of Cal/Val activities.</p><p>The L2A product will become publicly available during Spring 2021. Thus, this is also an opportunity to introduce a few practical aspects about its usage.</p>

Aeolus Rayleigh-channel winds in cloudy conditions

<p>Aeolus was launched in August 2018 and is expected to be operational until 2022. Aeolus is the first Doppler wind lidar in space to measure wind profiles through Rayleigh scattering of an ultra-violet laser beam and the determination of the Doppler shift of the scattered light by molecules along the Line-Of-Sight (LOS). In addition, Mie scattering provides winds on aerosol and cloud particles. The atmosphere return signal is a small bandwidth peak (from Mie scattering) on top of a broadband spectrum (from Rayleigh scattering). The tails and central part of the spectrum are being processed separately to yield so-called Rayleigh channel and Mie channel winds respectively.</p><p>Signals in both channels are being accumulated onboard the satellite to segments of 2.85 km length along the satellite track, denoted measurements. Rayleigh winds are obtained by on-ground processing through accumulating typically 30 measurements to yield a single Rayleigh wind observation of sufficient quality for use in Numerical Weather Prediction (NWP). The vertical resolution of the horizontally projected LOS wind profiles is typically 500 m in the boundary layer, 1 km in the free-troposphere and 1.5-2 km in the stratosphere, but this can and has been changed in a flexible way during the mission.</p><p>In case of clouds and/or aerosols presence within the sensing atmospheric volume, signal from Mie scattering leaks into the Rayleigh channel signal. Since the Rayleigh-channel signal processing assumes a pure molecular signal this so-called Mie contamination causes biases in retrieved winds. This is solved through classifying measurements as either ‘clear’ or ‘cloudy’ before accumulation to observation level. Clear measurements (out of a total of 30) are accumulated to yield a Rayleigh-clear wind. This procedure has proven successful and Aeolus Rayleigh-clear winds are used operationally today by a number of meteorological centers around the world.</p><p>A similar procedure for cloudy measurements is less trivial and requires correction for Mie contamination. So far, implemented corrections were not successful in producing Rayleigh-cloudy winds of sufficient quality for use in NWP. A new correction scheme has been introduced and tested recently and proved successful to produce bias-free winds and a random error slightly larger as compared to Rayleigh-clear winds. The latter is explained by increased heterogeneous atmospheric conditions in which Rayleigh-cloudy winds are obtained. Interestingly, Rayleigh-cloudy and Mie-cloudy winds are obtained for identical atmospheric conditions and as such provide independent information on the atmospheric flow, which allows to characterize the error sources of the different types of wind observations, including instrumental/calibration errors, but also errors due to incorrect height assignment and representativity.</p><p>This paper describes the new scheme to correct Rayleigh winds for Mie contamination and its application to Aeolus data. The results show that resulting Rayleigh-cloudy winds are of good quality to be considered for operational use in NWP.</p>