Microwave Filter Analysis with Hybrid Circuitry Structure using Wave Iterative Method

Author(s):  
Nattapong Intarawiset ◽  
Sarun Narongkul ◽  
Phouvieng Phathithak ◽  
Somsak Akatimagool

A microwave filter is a two-port component usually employed when there is a need to control the frequency response at any given point in a microwave system. They provide transmission at certain frequencies, which are known as the passband frequencies, and attenuation at other frequencies, which are referred to as the stopband frequencies. The frequencies outside the passband are attenuated or reflected. Microwave filter is often named after the polynomial used to form its transfer function (i.e., Chebyshev, Butterworth [or maximally flat], Elliptical, etc.). The filter can be further sub-divided into four categorises (i.e., lowpass, highpass, bandstop, and bandpass filters) according to its frequency responses. This chapter gives a detailed discussion on filter classification and transfer function. It also covers the analysis, design, and implementation of a test microwave filter using the 21st century SIW transmission line. The simulation and measurement results of the test filter is also presented, compared, and discussed.


Author(s):  
Galina Vasil’evna Troshina ◽  
Alexander Aleksandrovich Voevoda

It was suggested to use the system model working in real time for an iterative method of the parameter estimation. It gives the chance to select a suitable input signal, and also to carry out the setup of the object parameters. The object modeling for a case when the system isn't affected by the measurement noises, and also for a case when an object is under the gaussian noise was executed in the MatLab environment. The superposition of two meanders with different periods and single amplitude is used as an input signal. The model represents the three-layer structure in the MatLab environment. On the most upper layer there are units corresponding to the simulation of an input signal, directly the object, the unit of the noise simulation and the unit for the parameter estimation. The second and the third layers correspond to the simulation of the iterative method of the least squares. The diagrams of the input and the output signals in the absence of noise and in the presence of noise are shown. The results of parameter estimation of a static object are given. According to the results of modeling, the algorithm works well even in the presence of significant measurement noise. To verify the correctness of the work of an algorithm the auxiliary computations have been performed and the diagrams of the gain behavior amount which is used in the parameter estimation procedure have been constructed. The entry conditions which are necessary for the work of an iterative method of the least squares are specified. The understanding of this algorithm functioning principles is a basis for its subsequent use for the parameter estimation of the multi-channel dynamic objects.


PIERS Online ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 120-122 ◽  
Author(s):  
Jaimon Yohannan ◽  
Vinu Thomas ◽  
V. Hamsakutty ◽  
A. V. Praveen Kumar ◽  
K. T. Mathew

2018 ◽  
Vol 30 (10) ◽  
pp. 67-85
Author(s):  
V. Zhukov ◽  
◽  
O. Feodoritova ◽  
N. Novikova ◽  
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