No abstract

The twenty-first century is the era of electronic warfare and information warfare. The focus is of the battle between all parties. CEEMD can link the time domain and frequency domain, describe the two-dimensional time–frequency characteristics of the signal, and draw the time–frequency diagram of the signal, so as to reduce the noise signal and improve the signal-to-noise ratio of the signal. The purpose of this paper was to study how to adjust the signal square spectrum bandwidth ratio in the subject of identifying the intra-pulse modulation of radar, so as to solve the problem of identifying the type of radar intra-pulse modulation. The experimental results in this paper show that the decomposition result of EEMD is incomplete and the signal reconstruction error is larger. Compared with the previous two methods, not only the CEEMD method can effectively suppress modal aliasing, but also the decomposition result is complete; the signal reconstruction error is very small, and the decomposition results close to ideal value. The interleaving filter with a bandwidth ratio of 1:2 can divide the 100 GHz channel spacing into asymmetric output spectra with bandwidths greater than 60 GHz and 30 GHz, which effectively improves the current mix of 10 Gb/s and 40 Gb/s The bandwidth utilization of the system illustrates the success of the simulation experiment.

No abstract

The main goal of this paper is to suppress the effect of unavoidable colored Gaussian noise on declining accuracy of transistor 1/f spectrum estimation. Transistor noises are measured by a nondestructive cross-spectrum measurement method, which is first to amplify the voltage signals through ultra-low noise amplifiers, then input the weak signals into data acquisition card. The data acquisition card collects the voltage signals and outputs the amplified noise for further analysis. According to our studies, the output 1/f noise can be characterized more accurately as non-Gaussian a-stable distribution rather than Gaussian distribution. Therefore, by utilizing the properties of a-stable distribution, we propose a cross-spectrum method effective in noisy environments based on samples normalized cross-correlation function. Simulation results and diodes output noise spectrum estimation results confirm the effectiveness of our method.