Search

Computerized ionospheric tomography is a highly ill-posed inverse problem, and regularization tends to stabilize the problem to provide a unique solution. When a regularization method is used, the choice of an optimal parameter is a key issue. In this article, we propose an adaptive regularization method for 3-D ionospheric tomography based on the U-curve. The proposed approach uses a U-curve method to determine the optimal regularization parameter from Global Navigation Satellite Systems (GNSS) observation data. Comparative case studies are investigated based on GNSS simulated observations and real measurements. The simulation results indicate that the proposed method is superior to the adaptive regularization method based on the L-curve. In addition, we further validate the tomographic results with actual ionosonde station data. The results demonstrate the reliability and superiority of the proposed method compared to traditional methods. [ABSTRACT FROM AUTHOR]

This paper considers the joint design of transmit waveforms and receive filters for airborne multiple-input-multiple-output (MIMO) radar systems. The aim is to maximize the output signal-to-interference-plus-noise ratio (SINR) such that we can achieve enhanced detection performance for a slow-moving target that might be obscured by clutter and jamming. We devise a cyclic algorithm to tackle the non-convex joint design problem. Considering practical implementation issues, we extend the algorithm to deal with constrained designs (i.e., the design of waveforms under a constant-envelope constraint and a similarity constraint, respectively). The convergence of all the devised algorithms is guaranteed. We provide several numerical examples to demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

This paper investigated the bacterial inactivation/sterilization effects of a gas-liquid gliding arc discharge reactor, which created plasma at atmospheric pressure and ambient temperature. Bacteria Escherichia coli were subjected to plasma treatment and the survivability was examined. With the bacteria suspension circulated at defined flow rate, the E. coli cells were almost killed in <3 min. The inactivation efficiency with circulation was much higher than that with no circulation, and it could even reach a reduction of 7 logarithm units in the number of viable bacteria within 30 s after 1-min treatment. Flow rates of the suspension caused slightly impact on the bacteria inactivation to a certain extent. Observations of scanning electron microscopy images helped to draw a conclusion that gas-liquid gliding arc discharge plasma acts under various mechanisms driven essentially by oxidation and electric effect. The results demonstrate that gas-liquid gliding arc discharge allows a rapid and complete inactivation of E. coli bacteria in the water, which shows the great industrial interest of gliding arc discharge technique for decontamination. [ABSTRACT FROM PUBLISHER]

This paper presents the analysis, fabrication, and experimental results of wirelessly actuated chip-scale rotary motors. Two designs are described. Design M is actuated by a \phi 8-mm magnetoelastic stator lithographically micromachined from Metglas 2826MB-bulk-foil with 25 \mu\m thickness. It operates at a resonant frequency of 11.35 kHz while 3-Oe dc and 2-Oe amplitude ac magnetic fields are applied. The measured rotation speed, start torque, calculated driving step size, and payload are 44 r/min, 2 \nN \cdot \m, \approx23 mdeg, and 9 mg, respectively. Design S uses a stator that is a sandwich of Si (\phi 8 mm diameter and 65 \mu\m thickness) and magnetoelastic foil (\phi 8 mm diameter and 25 \mu\m thickness) to tailor the stiffness. The typical resonant frequencies of clockwise (CW) mode and counterclockwise (CCW) mode are 6.1 and 7.9 kHz, respectively. The CCW mode provides a rotation rate of about 100 r/min, start torque of 30 \nN \cdot \m, and driving step size of 74 mdeg while 8-Oe dc and 6-Oe amplitude ac magnetic fields are applied. Bidirectional rotation is realized by switching the applied frequency, thereby exciting the stator in a slightly different mode shape. Design S shows at least 43-mg payload capability. \hfill[2012-0207] [ABSTRACT FROM AUTHOR]

In order to investigate the clutter nulling performance of the sample matrix inversion (SMI) algorithm in amplitude heterogeneous environments, we derive an analytical expression for the average signal-to-interference plus noise ratio (SINR) loss based on random matrix theory. The results show that comparing with the case where the training data utilizes the homogeneous secondary samples (which are independent and identically distributed (IID) to the snapshot in the cell under test (CUT)), formulating the adaptive weight with the secondary samples which have stronger clutter power than that in CUT will increase the output SINR. Nevertheless, the achievable performance improvement might be quite limited. Conversely, selecting the secondary samples with weaker clutter power will degrade the performance. [ABSTRACT FROM AUTHOR]

This research considers an advanced pulse compression noise (APCN) radar waveform possessing salient features from linear-FM (LFM) and noise waveforms. A cross-correlation model considering several chirp waveform profiles is used to simulate the output of a passive electronic intelligence (ELINT) intercept-receiver. By doing so we are able to demonstrate the low probability of interception (LPI) characteristic of the APCN waveform for different $*gk$ values. [ABSTRACT FROM AUTHOR]

Previous work on multiple-input multiple-output (MIMO) radar waveform design in colored noise based on minimizing minimum mean-square error (MMSE) and normalized mean-square error (NMSE) only considered the optimization of the singular value of the waveform matrix, while the optimization of singular vectors, which forms a basis of singular value optimization, was not stressed enough. In this correspondence, we revisit the waveform design problem for MIMO radar in colored noise based on MMSE and NMSE respectively. Further results for the optimal solutions under both criteria are derived. We prove the optimality of “matching” with the target and colored noise for the singular vectors of the transmitted waveform. Moreover, to obtain minimum MMSE/NMSE, the pairing of the eigenvectors of the target and noise should be carefully designed, where the optimal pairing of the eigenvectors based on MMSE is fixed while the optimal pairing based on NMSE changes according to the transmitted power, the strength of the target, and noise. [ABSTRACT FROM PUBLISHER]

Space-time adaptive processing (STAP) is a popularly used strategy for clutter suppression in moving-platform radar. In this context, the estimate of the clutter covariance matrix (CCM) is usually required to derive a near-optimum processing. The problem of estimation convergence then arises, especially in heterogeneous clutter environments, where, in the case of low convergence, the limited number of training samples will result in significantly degraded performance. Recently proposed knowledge-aided (KA) approaches show strong capability in improving convergence. Such capability is shown here to be essentially due to the reduction on the number of degrees of freedom (NDoF) of the sample space of the clutter process that bounds the convergence. In addition, the convergence measure of effectiveness (MOE) of two primary KA approaches, i.e., colored loading (CL) and fast maximum likelihood with assumed clutter covariance (FMLACC), is theoretically analyzed. The application of covariance matrix tapers (CMT) is proposed to enhance their robustness against knowledge mismatches. The simulation verifies the conclusions. [ABSTRACT FROM AUTHOR]

To improve the seamless navigation ability of an integrated Global Positioning System (GPS)/inertial navigation system in GPS-denied environments, a hybrid navigation strategy called the self-learning square-root- cubature Kalman filter (SL-SRCKF) is proposed in this article. The SL-SRCKF process contains two innovative steps: 1) it provides the traditional SRCKF with a self-learning ability, which means that navigation system observations can be provided continuously, even during long-term GPS outages; and 2) the relationship between the current Kalman filter gains and the optimal estimation error is established, which means that the optimal estimation accuracy can be improved by error compensation. The superiority of the proposed SL-SRCKF strategy is verified via experimental results and prominent advantages of this approach include: 1) the SL-SRCKF comprises two cycle filtering systems that work in a tightly coupled mode, and this allows more accurate error correction results to be obtained during GPS outages; 2) the system's error prediction ability is effectively improved by introducing a long short-term memory, which provides much better performance than other neural networks, such as random forest regression or the recursive neural network; and 3) under different (30, 60, and 100 s) GPS outage conditions, the long-term stability of SL-SRCKF is much better than that of other error correction approaches. [ABSTRACT FROM AUTHOR]

A 2 T magnetic field system (second long) based on storage supercapacitor was designed and developed to fulfill the guiding magnetic field requirement of the high-power microwave devices. First, the basic principle of the supercapacitor magnetic field system was briefly introduced. Then the main parameters of the power supply and solenoid were discussed and calculated in detail. In the end, through the simulation and experiment, we verified that the magnetic field system based on supercapacitor could well meet guiding magnetic need. Finally, the roadblock and outlook of this magnetic system were analyzed generally. The method in this research would have certain reference value for the design of similar magnetic systems. [ABSTRACT FROM AUTHOR]