New method of time-frequency representation for ISAR imaging of ship targets

Inverse synthetic aperture radar （ISAR） imaging of ship targets is very important in the national defense. For the high maneuverability of ship targets, the Doppler frequency shift of the received signal is time-varying, which will degrade the ISAR image quality for the traditional range-Doppler （RD） algorithm. In this paper, the received signal in a range bin is characterized as the multi-component polynomial phase signal （PPS） after the motion compensation, and a new approach of time-frequency represen- tation, generalized polynomial Wigner-Ville distribution （GPWVD）, is proposed for the azimuth focusing. The GPWVD is based on the exponential matched-phase （EMP） principle. Compared with the conventional polynomial Wigner-Ville distribution （PWVD）, the EMP principle transfers the non-integer lag coefficients of the PWVD to the position of the exponential of the signal, and the interpolation can be avoided completely. For the GPWVD, the cross-terms between multi-component signals can be reduced by decomposing the GPWVD into the convolution of Wigner-Ville distribution （WVD） and the spectrum of phase adjust functions. The GPWVD is used in the ISAR imaging of ship targets, and the high quality instantaneous ISAR images can be obtained. Simulation results and measurement data demonstrate the effectiveness of the proposed new method.

Line spectrum detection algorithm based on the phase feature of target radiated noise

In order to improve the performance of line spectrum detection,according to the feature that the underwater target radiated noise containing stable line spectrum,the differences of the phase difference between line spectrum and background noise,a weighted line spectrum detection algorithm based on the phase variance is proposed in frequency domain.After phase difference alignment,the phase variance of line spectrum and the phase of background noise,respectively,are small and big in frequency domain,this method utilizes the weighted statistical algorithm to cumulate the frequency spectrum based on the phase variance,which can restrain the background noise disturbance,and enhance the signal to noise ratio（SNR）.The theory analysis and experimental results both verify that the proposed method can well enhance the energy of line spectrum,restrain the energy of background noise,and have better detection performance under lower SNR.

Is it time to rethink the Alzheimer's disease drug development strategy by targeting its silent phase?

Alzheimer＇s disease （AD） is the most frequent cause of dementia in the western world. In clinical terms, AD is characterized by progres- sive cognitive decline that usually begins with memory impairment. As the disease progresses, AD inevitably affects all intellectual functions including executive functions, leading to complete dependence for basic activities of daily life and premature death.

A high-order target phase approach for the station-keeping of periodic orbits

A novel high-order target phase approach(TPhA)for the station-keeping of periodic orbits is proposed in this work.The key elements of the TPhA method,the phase-angle Poincare map and high-order maneuver map,are constructed using differential algebra(DA)techniques to determine station-keeping epochs and calculate correction maneuvers.A stochastic optimization framework tailored for the TPhA-based station-keeping process is leveraged to search for fuel-optimal and error-robust TPhA parameters.Quasi-satellite orbits(QSOs)around Phobos are investigated to demonstrate the efficacy of TPhA in mutli-fidelity dynamical models.Monte Carlo simulations demonstrated that the baseline QSO of JAXA’s Martian Moons eXploration(MMX)mission could be maintained with a monthly maneuver budget of approximately 1 m/s.

Target recognition based on phase noise of received laser signal in lidar jammer

In this Letter, a method based on the effects of imperfect oscillators in lasers is proposed to distinguish targets in continuous wave tracking lidar. This technique is based on the fact that each lidar signal source has a specific influence on the phase noise that makes real targets from the false ones. A simulated signal is produced by complex circuits, modulators, memory, and signal oscillators. For example, a deception laser beam has an unequal and variable phase noise from a real target. Thus, the phase noise of transmitted and received signals does not have the same power levels and patterns. To consider the performance of the suggested method, the probability of detection（PD） is shown for various signal-to-noise ratios and signal-to-jammer ratios based on experimental outcomes.