Towards Self-supervised Learning for Multi-function Radar Behavior State Detection and Recognition

<div>The analysis of intercepted multi-function radar (MFR) signals has gained considerable attention in the field of cognitive electronic reconnaissance. With the rapid development of MFR, the switch between different work modes is becoming more flexible, increasing the agility of pulse parameters. Most of the existing approaches for recognizing MFR behaviors heavily depend on prior information, which can hardly be obtained in a non-cooperative way. This study develops a novel hierarchical contrastive self-supervise-based method for segmenting and clustering MFR pulse sequences. First, a convolutional neural network (CNN) with a limited receptive field is trained in a contrastive way to distinguish between pulse descriptor words (PDW) in the original order and the samples created by random permutations to detect the boundary between each radar word and perform segmentation. Afterward, the K-means++ algorithm with cosine distances is established to cluster the segmented PDWs according to the output vectors of the CNN’s last layer for radar words extraction. This segmenting and clustering process continues to go in the extracted radar word sequence, radar phase sequence, and so on, finishing the automatic extraction of MFR behavior states in the MFR hierarchical model. Simulation results show that without using any labeled data, the proposed method can effectively mine distinguishable patterns in the sequentially arriving PDWs and recognize the MFR behavior states under corrupted, overlapped pulse parameters.</div>

Towards Self-supervised Learning for Multi-function Radar Behavior State Detection and Recognition

<div>The analysis of intercepted multi-function radar (MFR) signals has gained considerable attention in the field of cognitive electronic reconnaissance. With the rapid development of MFR, the switch between different work modes is becoming more flexible, increasing the agility of pulse parameters. Most of the existing approaches for recognizing MFR behaviors heavily depend on prior information, which can hardly be obtained in a non-cooperative way. This study develops a novel hierarchical contrastive self-supervise-based method for segmenting and clustering MFR pulse sequences. First, a convolutional neural network (CNN) with a limited receptive field is trained in a contrastive way to distinguish between pulse descriptor words (PDW) in the original order and the samples created by random permutations to detect the boundary between each radar word and perform segmentation. Afterward, the K-means++ algorithm with cosine distances is established to cluster the segmented PDWs according to the output vectors of the CNN’s last layer for radar words extraction. This segmenting and clustering process continues to go in the extracted radar word sequence, radar phase sequence, and so on, finishing the automatic extraction of MFR behavior states in the MFR hierarchical model. Simulation results show that without using any labeled data, the proposed method can effectively mine distinguishable patterns in the sequentially arriving PDWs and recognize the MFR behavior states under corrupted, overlapped pulse parameters.</div>

Effects of pulse parameters on the temperature distribution of a human head exposed to the electromagnetic pulse

The presence of blood–brain barrier (BBB) is a major obstacle to effectively deliver therapeutics to the central nervous system (CNS); hence, the outcomes following treatment of CNS diseases remain unsatisfactory. Fortunately, electromagnetic pulses (EMPs) provide a non-invasive method to locally open the BBB. To obtain the optimal pulse parameters of EMP-induced BBB opening to ensure the effective delivery of CNS drugs, it is particularly important to measure and assess the effects of pulse parameters on the temperature distribution in the human head exposed to EMPs. In this paper, the specific anthropomorphic mannequin phantom was adopted and the temperature increase in the human head induced by EMPs of different parameters was estimated in the software “COMSOL Multiphysics”. The results show that the temperature distribution profiles with different EMP parameters have almost similar characteristics, the highest temperature increase values in the human head are positively correlated with variations of EMP parameters, and potential hazards to the human head may occur when EMP parameters exceed the safety threshold, which will provide theoretical basis for seeking the optimal EMP parameters to open the BBB to the greatest extent within a safe range.

Adaptive Nonlinear Phase Compensation in a Femtosecond Hybrid Laser with Varying Pulse Repetition Rate

In this manuscript, an implementation of a tunable nonlinear phase compensation method is demonstrated on a typical femtosecond hybrid laser consisting of a fiber pre-amplifier and an additional solid-state amplifier. This enables one to achieve constant laser pulse parameters over a wide range of pulse repetition rates in such a laser. As the gain in the solid-state amplifier is inversely proportional to the input power, the shortfall in the solid-state gain at higher repetition rates must be compensated for with fiber pre-amplifier to ensure constant pulse energy. This increases the accumulated nonlinear phase and consequently alters the laser pulse parameters such as pulse duration and Strehl ratio. To overcome this issue, the nonlinear phase must be compensated for, and what is more it should be compensated for to a different extent at different pulse repetition rates. This is achieved with a tunable CFBG, used also as a pulse stretcher. Using this concept, we demonstrate that constant laser pulse parameters such as pulse energy, pulse duration and Strehl ratio can be achieved in a hybrid laser regardless of the pulse repetition rate.

Long-Lasting Orientation of Symmetric-Top Molecules Excited by Two-Color Femtosecond Pulses

Impulsive orientation of symmetric-top molecules excited by two-color femtosecond pulses is considered. In addition to the well-known transient orientation appearing immediately after the pulse and then reemerging periodically due to quantum revivals, we report the phenomenon of field-free long-lasting orientation. Long-lasting means that the time averaged orientation remains non-zero until destroyed by other physical effects, e.g., intermolecular collisions. The effect is caused by the combined action of the field-polarizability and field-hyperpolarizability interactions. The dependence of degree of long-lasting orientation on temperature and pulse parameters is considered. The effect can be measured by means of second (or higher-order) harmonic generation, and may be used to control the deflection of molecules traveling through inhomogeneous electrostatic fields.

Novel Optical Solitons to the Perturbed Gerdjikov-Ivanov Equation Via Collective Variables

The objective of this research is to study the collective variable (CV) technique to explore an important form of Schrödinger equation known as the Gerdjikov-Ivanov (GI) equation which expresses the dynamics of solitons for optical fibers in terms of pulse parameters. These parameters are temporal position, amplitude, width, chirp, phase, and frequency known as collective variables (CVs). This is an effective and dynamic mathematical gadget to obtain soliton solutions of non-dimensional as well as perturbed GI equations. Moreover, an established numerical scheme that is the fourth-order Runge-Kutta method is exerted for the numerical simulation of the revealing coupled system of six ordinary differential equations which represent all the CVs included in the pulse ansatz. The CV approach is used to determine the evolution of pulse parameters with the propagation distance and illustrated it illustrated it graphically. Furthermore, Figures show the compelling periodic oscillations of pulse chirp, width, frequency and amplitude of soliton. For various values of super-Gaussian pulse parameters, the numerical behavior of solitons to illustrate variations in CVs is provided. Other significant aspects with regards to the current investigation are also inferred.