Analysis and Mitigation of Crosstalk Effect on Coastal GNSS-R Code-Level Altimetry Using L5 Signals from QZSS GEO

Coastal Global Navigation Satellite System Reflectometry (GNSS-R) can be used as a valuable supplement for conventional tide gauges, which can be applied for marine environment monitoring and disaster warning. Incidentally, an important problem in dual-antenna GNSS-R altimetry is the crosstalk effect, which means that the direct signal leaks into the down-looking antenna dedicated to the reflected signals. When the path delay between the direct and reflected signals is less than one chip length, the delay waveform of the reflected signal is distorted, and the code-level altimetry precision decreases consequently. To solve this problem, the author deduced the influence of signal crosstalk on the reflected signal structure as the same as the multipath effect. Then, a simulation and a coastal experiment are performed to analyze the crosstalk effect on code delay measurements. The L5 signal transmitted by the Quasi-Zenith Satellite System (QZSS) from a geosynchronous equatorial orbit (GEO) satellite is used to avoid the signal power variations with the elevation, so that high-precision GNSS-R code altimetry measurements are achieved in the experiment. Theoretically and experimentally, we found there exists a bias in proportion to the power of the crosstalk signals and a high-frequency term related to the phase delay between the direct and reflected signals. After weakening the crosstalk by correcting the delay waveform, the results show that the RMSE between 23-h sea level height (SSH) measurements and the in-situ observations is about 9.5 cm.

Global solvability and asymptotic stabilization in a three-dimensional Keller–Segel–Navier–Stokes system with indirect signal production

This paper deals with the Keller–Segel–Navier–Stokes model with indirect signal production in a three-dimensional (3D) bounded domain with smooth boundary. When the logistic-type degradation here is weaker than the usual quadratic case, it is proved that for any sufficiently regular initial data, the associated no-flux/no-flux/no-flux/Dirichlet problem possesses at least one globally defined solution in an appropriate generalized sense, and that this solution is uniformly bounded in [Formula: see text] with any [Formula: see text]. Moreover, under an explicit condition on the chemotactic sensitivity, these solutions are shown to stabilize toward the corresponding spatially homogeneous state in the sense of some suitable norms. We underline that the same results were established for the corresponding system with direct signal production in a well-known result if the degradation is quadratic. Our result rigorously confirms that the indirect signal production mechanism genuinely contributes to the global solvability of the 3D Keller–Segel–Navier–Stokes system.

Clutter cancellation in passive radar using batch-based CLEAN technique

Passive radar (PR) systems need to detect the presence of a target response, which is many orders of magnitude weaker than the clutter (direct signal and multipath). Indeed, the clutter cancellation is a key stage within a PR processing scheme. One of the most effective techniques in this field is using the CLEAN approach. In this paper, the batch-based CLEAN technique based on GMP and FFT has been proposed, which can speed up the computational processing and have better cancellation gain. Furthermore, segmenting operation can be applied to the signal obtained over long time. It is helpful to enhance temporal or spatial efficiency and overcome effect of time-varying clutter. Experiment results with simulated and real passive radar data verify the effectiveness of the proposed algorithm.

A Low Computational Complexity DOA Estimation using Sum/difference Pattern based on DNN

Tracking low-elevation targets over an uneven surface is challenging because of the complicated and volatile multipath signals. Multipath signals cause the amplitude and phase distortion of direct signal, which degrades the performance and generates mismatch between existing classical multipath signal and actual model. Machine learning-based methods are data-driven, they do not rely on prior assumptions about array geometries, and are expected to adapt better to array imperfections. The amplitude comparison Direction-of-Arrival (DOA) algorithm performs a few calculations, has a simple system structure, and is widely used. In this paper, an efficient DOA estimation approach based on Sum/Difference pattern is merged with deep neural network. Fully learn the potential features of the direct signal from the echo signal. In order to integrate more phase features, the covariance matrix is applied to the amplitude comparison algorithm, it can accommodate multiple snapshot signals instead of a single pulse automatically. The outputs of the deep neural network (DNN) are concatenated to reconstruct a covariance matrix for DOA estimation. Moreover, the superiority in computational complexity and generalization of proposed method are proved by simulation experiments compared with state-of-the-art physics-driven and data-driven methods. Field data sets acquired from a VHF array radar are carried out to verify the proposed method satisfies practicability in the severe multipath effect.

FSR Systems for Detection of Air Objects Using Cosmic Radio Emissions

The paper analyses the possibility of Forward Scatter Radar (FSR) systems to detect airplanes using cosmic emission from pulsars and planets (pulsar, Sun, Moon). A suboptimal multichannel algorithm for joint detection and evaluation of the parameters of the forward scattering signal created by an airplane (duration and velocity) is proposed, with preliminary compensation of the powerful direct signal emitted by cosmic sources (pulsar, Sun and Moon). The expressions for calculation of the Signal-to-Noise Ratio (SNR) at the input of the detector and the compensator are obtained. The detection characteristics are also obtained, and the requirements for the suppression coefficient of the compensator are evaluated. A methodology for calculating the maximum distance for detecting an aircraft using a described algorithm is proposed. The obtained results show that due to the Forward Scatter (FS) effect, there is the theoretical possibility to detect airplanes at close ranges by FSRs, which use very weak signals from cosmic sources.

On the multipath effects due to wall reflections for wave reception in a corner

Multipath effects occur when receiving a wave near a corner, for example, the noise of an helicopter or an aircraft or a drone or other forms of urban air mobility near a building, or a telecommunications receiver antenna near an obstacle. The total signal received in a corner consists of four parts: (i) a direct signal from source to observer; (ii) a second signal reflected on the ground; (iii) a third signal reflected on the wall; (iv) a fourth signal reflected from both wall and ground. The problem is solved in two-dimensions to specify the total signal, whose ratio to the direct signal specifies the multipath factor. The amplitude and phase of the multipath factor are plotted as functions of the frequency over the audible range, for various relative positions of observer and source, and for several combinations of the reflection coefficients of the ground and wall. It is shown that the received signal consists of a double series of spectral bands, in other words: (i) the interference effects lead to spectral bands with peaks and zeros; (ii) the successive peaks also go through zeros and “peaks of the peaks”. The results apply not only to sound, but also to other waves, e.g., electromagnetic waves using the corresponding frequency band and reflection factors.