Improvement of Intercept Probability Algorithm for Anti-ship Missile Based on Search Theory

Traditional intercept probability model has some drawbacks and can not meet the demands of command and control system. Aiming at this problem, a new calculation method based on search theory, terminal control area distribution function of anti-ship missile, target distribution function and missile's radar scan feature is proposed. Under the condition of common target distribution, an intercept probability model for present point attacking is determined. The simulation verifies its effectiveness and establishes the selecting model for aiming point when enemy ships evade in high speed.

Influencing factor analysis of interception probability and classification-regression neural network based estimation

The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.

Interception probability simulation and analysis of salvo of two electromagnetic coil launched anti-torpedo torpedoes

Electromagnetic coil launch is an important branch of electromagnetic launch(EML)technology,which is suitable for launching anti-torpedo torpedo(ATT).This paper focuses on the EML parameters and the interception probability of the EML two ATTs salvo.Based on the launching model of a multi-stage coil launcher,the trajectory model of the ATT and the attacking torpedo,a calculation method for the EML two ATTs salvo parameters is proposed,with the conditions of capture and interception given reasonably.An adaptive particle swarm optimization(APSO)algorithm is proposed to calculate the optimal launching parameters,by designing the adaptive inertia weight and time-varying study factors.According to the analysis of the simulation with Monte Carlo method,EML will improve the interception probability effectively,and the interception probability is affected by the launching range.The results demonstrate good performance of the proposed APSO in calculating EML parameters for the two ATTs salvo in certain combat situation.Implications of these results are particular regarding the command and decision in the anti-torpedo combat.

Sensor radiation interception risk control in target tracking

This paper is mainly on the problem of radiation interception risk control in sensor network for target tracking.Firstly,the sensor radiation interception risk is defined as the product of the interception probability and the cost caused by the interception.Secondly,the radiation interception probability model and cost model are established,based on which the calculation method of interception risk can be obtained.Thirdly,a sensor scheduling model of radiation risk control is established,taking the minimum interception risk as the objective function.Then the Hungarian algorithm is proposed to obtain sensor scheduling scheme.Finally,simulation experiments are mad to prove the effectiveness of the methods proposed in this paper,which shows that compared with the sensor radiation interception probability control method,the interception risk control method can keep the sensor scheduling scheme in low risk as well as protect sensors of importance in the sensor network.

Self-adapting radiation control method for RFS in tracking

The aim of this paper is to achieve the radio frequency stealth(RFS) during the course of tracking by controlling the radiation energy and the interval of a radar. Firstly, we build the model of probability of interception with the once radiation during the course of tracking. Secondly, we establish the model of the cumulative probability of interception to describe the effect of RFS throughout the tracking process and obtain two solutions that are minimizing the probability of interception and the radiation times to reduce the cumulative probability of interception. Thirdly, we propose a self-adapting radiation energy control method(SARE)to minimize the probability of interception. Fourthly, we propose a self-adapting radiation interval control method(SARI) to minimize radiation times. Fifthly, combining SARE with SARI, we propose a SARE-SARI control method(SAEI) during the course of tracking.Finally, we compare SAEI with two others by simulation, and the results show the effect of RFS of SAEI is better than the other two,but we have to make a trade-off between the ability of RFS and the effect of tracking.

LPI radar signal detection based on the combination of FFT and segmented autocorrelation plus PAHT

This paper proposes a desirable method to detect different kinds of low probability of intercept (LPI) radar signals, targeted at the main intra-pulse modulation method of LPI radar signals including the signals of linear frequency modulation, phase code, and frequency code. Firstly, it improves the coherent integration of LPI radar signals by adding the periodicity of the ambiguity function. Then, it develops a frequency domain detection method based on fast Fourier transform (FFT) and segmented autocorrelation function to detect signals without features of linear frequency modulation by virtue of the distribution characteristics of noise signals in the frequency domain. Finally, this paper gives a verification of the performance of the method for different signal-to-noise ratios by conducting simulation experiments, and compares the method with existing ones. Additionally, this method is characterized by the straightforward calculation and high real-time performance, which is conducive to better detecting all kinds of LPI radar signals.

Research on LPI radar signal detection and parameter estimation technology

Modern radar signals mostly use low probability of intercept(LPI)waveforms,which have short pulses in the time domain,multicomponent properties,frequency hopping,combined modulation waveforms and other characteristics,making the detection and estimation of LPI radar signals extremely difficult,and leading to highly required significant research on perception technology in the battlefield environment.This paper proposes a visibility graphs(VG)-based multicomponent signals detection method and a modulation waveforms parameter estimation algorithm based on the time-frequency representation(TFR).On the one hand,the frequency domain VG is used to set the dynamic threshold for detecting the multicomponent LPI radar waveforms.On the other hand,the signal is projected into the time and frequency domains by the TFR method for estimating its symbol width and instantaneous frequency(IF).Simulation performance shows that,compared with the most advanced methods,the algorithm proposed in this paper has a valuable advantage.Meanwhile,the calculation cost of the algorithm is quite low,and it is achievable in the future battlefield.

Novel sensor selection strategy for LPI based on an improved IMMPF tracking method

Sensor platforms with active sensing equipment such as radar may betray their existence, by emitting energy that will be intercepted by enemy surveillance sensors. The radar with less emission has more excellent performance of the low probability of intercept（LPI）. In order to reduce the emission times of the radar, a novel sensor selection strategy based on an improved interacting multiple model particle filter（IMMPF） tracking method is presented. Firstly the IMMPF tracking method is improved by increasing the weight of the particle which is close to the system state and updating the model probability of every particle. Then a sensor selection approach for LPI takes use of both the target＇s maneuverability and the state＇s uncertainty to decide the radar＇s radiation time. The radar will work only when the target＇s maneuverability and the state＇s uncertainty exceed the control capability of the passive sensors. Tracking accuracy and LPI performance are demonstrated in the Monte Carlo simulations.

Resource-saving scheduling scheme for centralized target tracking in multiple radar system under automatic blanket jamming

This paper investigates the problem of Joint Radar Node Selection and Power Allocation(JRNSPA)in the Multiple Radar System(MRS)in the blanket jamming environment.Each radar node independently tracks moving target and subsequently transmits the raw observation data to the fusion center,which formulates a centralized tracking network structure.In order to establish a practical blanket jamming environment,we suppose that each target carries the self-defense jammer which automatically implements blanket jamming to the radar nodes that exceed the preset interception probability.Subsequently,the Predicted Conditional Cramer-Rao Lower Bound(PC-CRLB)is derived and utilized as the tracking accuracy criterion.Aimed at ensuring both the tracking performance and the Low Probability of Intercept(LPI)performance,the resource-saving scheduling model is formulated to minimize the transmit power consumption while meeting the requirements of tracking accuracy.Finally,the Modified Zoutendijk Method Of Feasible Directions(MZMFD)-based two-stage solution technique is adopted to solve the formulated non-convex optimization model.Simulation results show the effectiveness of the proposed JRNSPA scheme.

A new evaluation model of comprehensive radio frequency stealth performance of radar

The detection capabilities of passive electronic warfare reconnaissance equipment have substantially increased during recent years.Correspondingly,the radar equipment is required to take various means to improve the radio frequency(RF)stealth performance to ensure the transmitted RF signal does not get intercepted.However,traditional evaluation methods on RF stealth performance cannot accurately evaluate the RF stealth capabilities of new system radar.In this study,a joint interception probability evaluation model on RF stealth performance was established,which divided the interception process into two parts:front interception and system interception.Various RF stealth means adopted by different radar equipment were taken into consideration to improve the applicability of this model.Simulation results show that this model is able to effectively characterize almost all the aspects of the RF stealth features and can serve as a good reference to evaluate RF radar stealth performance comprehensively.