An iterative algorithm calculates the embedded element pattern
A novel iterative method is proposed to process the transformation of the embedded element pattern or EEP. This technique modifies a group of patterns originated by a uniformly distributed load on the ports of an antenna, adapting them to a scenario with a non-uniform load. 🛰️
Foundation of the iterative method
The procedure stands out for its utility in inverting the calculations and determining the values of any type of load, starting only with the minimum indispensable amount of EEP patterns. This approach avoids the unnecessary repetition inherent in techniques that depend on matrices and leads to a process for identifying impedance faults that is numerically robust.
Main features of the algorithm:- Transforms uniform load patterns into non-uniform load patterns.
- Operates with the minimum necessary number of EEP patterns, eliminating redundancy.
- Provides numerical stability when calculating impedance mismatches.
The algorithm's convergence suggests the minimum signal-to-noise ratio and fading level that the measurement equipment must withstand.
Validation with presence of noise
Since EEPs are expected to be obtained mainly through measurement, the algorithm is tested by incorporating various noise components. Its convergence is analyzed, which indicates the minimum signal-to-noise ratio and attenuation level that the measurement instrument must handle. The analysis also points out how to best select the reference antenna to minimize error when estimating parameters. 📊
Key aspects of the validation:- The robustness of the method is tested by including noise in the input data.
- The convergence study defines requirements for the measurement equipment.
- Criteria are established for selecting the reference antenna and optimizing results.
Optimization of fault diagnosis
By requiring only the minimum number of patterns, the iterative technique simplifies the diagnosis process. This enables detecting impedance faults in antenna systems in a more effective and robust way, even when the input data contains the typical noise from measurements in real conditions. If your method converges more slowly than an administrator updating servers on a Friday afternoon, you might need to review the reference antenna configuration. 🔧