Modeling and Simulation for the Investigation of Radar Responses to Electronic Attacks in Electronic Warfare Environments

Abstract

An electronic warfare (EW) simulator is presented to investigate and evaluate the tracking performance of radar system under the electronic attack situations. The EW simulator has the input section in which the characteristic parameters of radar threat, radar warning receiver, jammer, electromagnetic wave propagation, and simulation scenario can be set up. During the process of simulation, the simulator displays the situations of simulation such as the received signal and its spectrum, radar scope, and angle tracking scope and also calculates the transient and root-mean-squared tracking errors of the range and angle tracking system of radar. Using the proposed EW simulator, we analyze the effect of concealment according to the noise and signal powers under the noise jamming and also analyze the effect of deception by calculating errors between the desired value and the estimated one under the deceptive jamming. Furthermore, the proposed EW simulator can be used to figure out the feature of radar threats based on the information collected from the EW receiver and also used to carry out the electronic attacks efficiently in electronic warfare.

Improvement of Performance Analysis of Amplitude-Comparison Monopulse Algorithm in the Presence of an Additive Noise

“…The elevation estimation equation based on Taylor approximation can also be obtained in the same way as the azimuth. The signs of n B and n D of the elevation estimation Equation (15) are opposite to the signs of n B and n D of the azimuth estimation Equation (14).…”

“…To obtain the MSE, the mean operation is applied to the square of the estimated angle. However, since (14) and (15) are nonlinear functions shown in a fractional form, it is difficult to develop the mean operation analytically. Therefore, by applying Taylor's approximation, which approximates this function as a polynomial function for n A , n B , n C , and n D , the analytical expansion of the mean operation is performed.…”

“…In Figure 3, empirical MSEs of (SAo), (SA'), (SA1), (SA2), and (SA3) are calculated from (17). In Figure 3, the result with legend (SAo) is obtained from (16), and the result with legend (SA') is obtained from (14). In Figure 3, the angle estimation equation used for (SA1) is (A10), and the angle estimation equation used for (SA2) is (A12).…”

Intelligent Data Fusion and Multi-Agent Coordination for Target Allocation

“…From the approaches for modeling and simulation of military-relevant robots in the field of simulated battlefield environments [4,16], several simulation systems emphasizing situation awareness were constructed. Parasuraman et al [5] designed a robotic simulation to complete several tasks including target identification task within a situation map.…”

Simulation for the Reverse Extrapolation of Radar Threats and their Verification

“…The functional modules of radar threat including antenna, intermediate frequency (IF) conversion, automatic gain control (AGC), constant false alarm rate (CFAR) detection, range tracking with early/late gates, angle tracking using monopulse method, and velocity estimation with narrow-band filter banks have been considered for a realistic design with reference to the theoretical models or the principles of circuit operation [12] of radar threats in the MATLAB simulator. In order to implement the propagation of electromagnetic waves in the MATLAB simulator, we have used the models in References [4,13,14] for the loss and attenuation of a transmitted electromagnetic wave, and those in Reference [4] for Doppler and multi-path fading effects which a transmitted wave suffers.…”