AN ANECHOIC CHAMBER BUILT INTO INDUSTRIAL ROOMS

The issues of designing anechoic chambers for antenna measurements of a certain type – em-bedded in the premises of industrial purpose are considered. The advantage of such chambers is a positive economic effect associated with both the reduction of costs for construction work, and with the possibility of joint use of auxiliary room systems in the process of operation. Known ap-proaches to the design of chambers for antenna measurements are based either on ensuring a min-imum level of aesthetics, or minimum overall dimensions. In this case, it is necessary to provide a compromise between the parameters of anechoic stability and overall dimensions while ensuring the technological accessibility of the entire usable area of the room. Aim. The aim of the work is to justify the form and geometric dimensions of the chamber. Research Methods. In the process of re-search used the methods of geometric optics. When justifying the form of the chamber, practical aspects were taken into account, namely, the common form of industrial premises and workshops, as well as the possibility of effective use of common radio-absorbing materials to cover the cham-ber from the inside. In the process of finding the optimal effective geometric dimensions, the quality functionals were assumed to be aechoic and dimensional parameters. Results. A chamber in the form of a rectangular trapezoid is optimal for embedding in industrial premises. The expressions for the geometric dimensions of the chamber, ensuring the absence of first- and second-order reflections in the working area, have been found. The optimum value of the deflection angle of the back wall of the anechoic chamber was found. Conclusion. Based on the above technique, an anechoic chamber of a compact range for antenna measurements has been realized.

On the Formulation and Implementation of the Love's Constraint for the Source Reconstruction Method

The formulation and implementation of the Love's condition constraint for the source reconstruction method (SRM) in near-field antenna measurements is analyzed in the context of inverse problems. To this end, the SRM is first analyzed to identify the non-unique or non-radiating current sources which may be present. Next, the advantages and disadvantages of general regularization techniques, which may address the non-radiating currents, are presented which serve to motivate the use of the Love's condition constraint. The main methods of formulating the constraint are then presented, one of which is a novel technique developed for this paper. Following this, the formulation methods are analyzed in order to predict the similarities and differences of the methods in the context of addressing the non-radiating currents of the SRM. This analysis is reinforced by simulated antenna measurements. In particular, the novel formulation method is demonstrated to provide greater reconstruction accuracy (in the examples considered), at the cost of computational complexity.

On the Formulation and Implementation of the Love's Constraint for the Source Reconstruction Method

The formulation and implementation of the Love's condition constraint for the source reconstruction method (SRM) in near-field antenna measurements is analyzed in the context of inverse problems. To this end, the SRM is first analyzed to identify the non-unique or non-radiating current sources which may be present. Next, the advantages and disadvantages of general regularization techniques, which may address the non-radiating currents, are presented which serve to motivate the use of the Love's condition constraint. The main methods of formulating the constraint are then presented, one of which is a novel technique developed for this paper. Following this, the formulation methods are analyzed in order to predict the similarities and differences of the methods in the context of addressing the non-radiating currents of the SRM. This analysis is reinforced by simulated antenna measurements. In particular, the novel formulation method is demonstrated to provide greater reconstruction accuracy (in the examples considered), at the cost of computational complexity.