Statistical Characterization of the Magnetic Field in Space during Magnetic Storms

Chen

2023

Sensors

Self Cite

Adaptive array processing technology for a phased array radar is usually based on the assumption of a stationary environment; however, in real-world scenarios, nonstationary interference and noise deteriorate the performance of the traditional gradient descent algorithm, in which the learning rate of the tap weights is fixed, leading to errors in the beam pattern and a reduced output signal-to-noise ratio (SNR). In this paper, we use the incremental delta-bar-delta (IDBD) algorithm, which has been widely used for system identification problems in nonstationary environments, to control the time-varying learning rates of the tap weights. The designed iteration formula for the learning rate ensures that the tap weights adaptively track the Wiener solution. The results of numerical simulations show that in a nonstationary environment, the traditional gradient descent algorithm with a fixed learning rate has a distorted beam pattern and reduced output SNR; however, the IDBD-based beamforming algorithm, in which a secondary control mechanism is used to adaptively update the learning rates, showed a similar beam pattern and output SNR to a traditional beamformer in a Gaussian white noise background; that is, the main beam and null satisfied the pointing constraints, and the optimal output SNR was obtained. Although the proposed algorithm contains a matrix inversion operation, which has considerable computational complexity, this operation could be replaced by the Levinson–Durbin iteration due to the Toeplitz characteristic of the matrix; therefore, the computational complexity could be decreased to O(n), so additional computing resources are not required. Moreover, according to some intuitive interpretations, the reliability and stability of the algorithm are guaranteed.

Section: Conclusion and Discussionmentioning

confidence: 99%

IDBD-Based Beamforming Algorithm for Improving the Performance of Phased Array Radar in Nonstationary Environments

Chen

2023

Sensors

Self Cite

“…As a final note, intermittency of the large scales (velocity, induction, temperature, density), as opposed to the small scales (vorticity, current, temperature or density gradients) has also been found in many contexts in the presence of waves [105][106][107][108] , as well as in the solar wind 72,109 and in magnetic storms 110 . For example, in stratified turbulence, the vertical velocity can have high kurtosis in a narrow range of the governing weak turbulence parameter, i.e.…”

Section: Exact Laws and Measurements Of Intermittencymentioning

confidence: 95%

The role of field correlations on turbulent dissipation

Pouquet¹

2023

Preprint

Nonlinear phenomena and turbulence are central to our understanding and modeling the dynamics of fluids and plasmas, and yet they still resist analytical resolutions in many instances. However, progress has been made recently, displaying a richness of phenomena which was somewhat unexpected a few years back, such as the double constant-flux cascades of a same invariant to both the large and to the small scales, or the presence of non-Gaussian wings in the large-scale fields, for fluids and plasmas. Here, I will concentrate on the direct measurement of the magnitude of dissipation and an evaluation of intermittency in a turbulent plasma using exact laws stemming from invariance principles and involving cross-correlation tensors with both the velocity and the magnetic fields. I will illustrate these points through scaling laws, together with data analysis from existing experiments, observations and numerical simulations. Finally, I will also briefly explore the possible implications for validity and use of several modeling strategies. To appear, Plasma Physics & Controlled Fusion, 2023.

Plasma Phys. Control. Fusion

“…In a final note, intermittency of the large scales (velocity, induction, temperature, and density), as opposed to the small scales (vorticity, current, temperature or density gradients) has also been found in many contexts in the presence of waves [105][106][107][108], as well as in the solar wind [72,109] and in magnetic storms [110]. For example, in stratified turbulence, the vertical velocity can have high kurtosis in a narrow range of the governing weak turbulence parameter, i.e.…”

Section: Exact Laws and Measurements Of Intermittencymentioning

confidence: 95%

The role of field correlations on turbulent dissipation

Pouquet

2023

Nonlinear phenomena and turbulence are central to our under- standing and modeling the dynamics of fluids and plasmas, and yet they still resist analytical resolutions in many instances. However, progress has been made recently, displaying a richness of phenomena which was somewhat unex- pected a few years back, such as the double constant-flux cascades of a same invariant to both the large and to the small scales, or the presence of non- Gaussian wings in the large-scale fields, for fluids and plasmas. Here, I will concentrate on the direct measurement of the magnitude of dissipation and an evaluation of intermittency in a turbulent plasma using exact laws stemming from invariance principles and involving cross-correlation tensors with both the velocity and the magnetic fields. I will illustrate these points through scal- ing laws, together with data analysis from existing experiments, observations and numerical simulations. Finally, I will also briefly explore the possible im- plications for validity and use of several modeling strategies.