The Optimization Design Of RF Passive Matching Filters

Communication and electronic systems generally consist of various equipment, In actual work, the systems usually meet the unmatched problem in impedance, namely the output impedance of the front equipment is unequal to the input impedance of the latter equipment. If they are directly connected, the circuit will not get the good power and cause other kinds of complicated circuit problems (such as the aberrance of the signal, reflecting loss etc.). The unmatched between the transmitter and the antenna is of such matter. It is more difficult for all systems to realize the matching by changing the parameters of the antenna or transmitter in actual. With the general network synthesis method, this problem can hardly be solved. If a passive matching network is added in the unmatched impedance, the problem will be solved. As a result, the matching network plays a key role in electronic and communication systems.Matching and filtering usually coexist, so a system is designed to combine the two problems together. The network model is used in this system in order to reduce the number of passive components or native components, to simplify the electric circuit, the input and output of the network. In this thesis, they are combined together to design the matching filter. In other words, it is designed directly.The traditional method of designing filter needs the complex deduction and computation, the formula of the terminal characteristic. It is more difficult for the engineering application to realize. In this thesis, circuit optimization technique is used to design LC passive matching network, and to change the actual load impedance into the impedance that needed and thus obtain the requested characteristic (such as amplitude frequency, standing wave ratio). The concrete steps are as follows: first, according to the demands of the filter and the matching, the traditional method is used to obtain the original value of the circuit, formulate the objective function for the optimization, and deduce the gradient of the objective function;second, optimization means is chosen to adjust the parameters to obtain the best parameters of the matching filter. Finally, an example is used to demonstrate the optimization effect of this method.