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Banerjee - Automated Electronic Filter Design

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Banerjee Automated Electronic Filter Design
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Springer International Publishing Switzerland 2017
Amal Banerjee Automated Electronic Filter Design 10.1007/978-3-319-43470-4_1
1. Introduction and Problem Statement
Amal Banerjee 1
(1)
Analog Electronics, Kolkata, India
Keywords
Electronic filter design Normalized filter Prototype filter Filter transformation SPICE Design space Performance evaluation
With the worldwide proliferation of wireless communication networks, precision analog signal processing is becoming more and more important each day. A crucial component of analog signal processing is signal filtering, thus the need for designing/implementing electronic filters that accurately satisfy design specifications (cutoff frequency, pass/stop band ripple, bandwidth, group delay/phase shift, etc.). This book elaborates on an automated, efficient, and yet very powerful scheme for designing/implementing and evaluating/fine-tuning performance characteristics of electronic filters. As all digital filters are derived from analog filters, this scheme can be extended to the digital filter domain easily.
In a nutshell, this scheme circumvents some key but complicated, manual (thus error-prone and time-consuming) steps of the traditional electronic filter design process. Easily automated (in this case is an ANSI C language program), the output is in the universally used circuit simulator SPICE input format. The filter designer can then easily evaluate and fine-tune the performance characteristics of the new filter design. A brief overview of the traditional electronic filter design process is presented to explain how this proposed scheme achieves its goal.
Briefly, traditional filter design process consists of the following steps, in that order:
  1. Basic loop equations are derived from Kirchhoffs current/voltage laws (KCL/KVL). These loop equations are differential equations, sometimes nonlinear. Typically, these differential equations are converted to more tractable algebraic equations, using Laplace transforms, effectively going from the time to frequency domain.
  2. In the filter transfer function H ( s ), the Laplace transform of the unit impulse response of the filter is obtained by evaluating H ( s ) at s = jw (in general, s = a + jw and s = jw represent a pure sinusoidal input). For calculation purposes, it is the ratio of the output to the input voltage in the frequency domain. The transfer function is almost always in a denominator-numerator polynomial form. The goal is to determine the roots of these two polynomials in the complex s -plane to obtain the poles and zeros. Poles and zeros are, respectively, the roots of the denominator and numerator polynomials. Only poles in the left half of the complex s -plane guarantee filter stability and need to be complex conjugates of each other to ensure real-valued coefficients in the differential equations representing the filter. Most importantly, for the generic case, the pole (and zero) values are analytical expressions involving the capacitors, inductors, and resistors to be used in the filter. Both the denominator and numerator polynomials need to be factorized to extract the zeros and poles of the transfer function. Sometimes, instead of using the transfer function, expressions for the filter insertion loss or loss magnitude versus frequency are used [], but that scheme involves first evaluating the loss expression in terms of the filter component values and then using a judicious combination of heuristics, ladder network, and precalculated table values.
  3. The most difficult step is to use the values of the poles and zeros evaluated previously and to determine values of each of the resistive and reactive components (capacitors, inductors) in the filter circuit. In the generic case, using the analytical expressions for the values of poles and zeros in combination with the predefined numerical values of design specifications (cutoff frequency, pass/stop band ripple, etc.) is an extremely complicated, manual, and thus error-prone/time-consuming/trial-and-error process. The designer can also utilize the causality and stability conditions and set resistor values to 1 to aid/simplify this calculation. Clearly, this step is feasible for low-order filters only.
To illustrate the issues involved, consider a third-order low pass filter, consisting only of passive components as capacitors ( C 1, C 3), inductors ( L 2), and resistors ( R L, R S), Fig..
Fig 11 Third-order low pass filter with passive components GND is signal - photo 1
Fig. 1.1
Third-order low pass filter with passive components. GND is signal ground
The generalized or generic transfer function for this filter is
11 The generalized transfer function is a cubic equation in s with - photo 2
(1.1)
The generalized transfer function () is a cubic equation in s , with real and imaginary roots. Once the analytical expressions for the transfer function roots and zeros are determined, the numerical values of the capacitors, inductors, and resistors have to be calculated, using predefined numerical values for the cutoff frequency, pass/stop band ripple, etc., and conditions of filter stability. This is another manual , time-consuming , and very error-prone calculation step . The design task is not complete until the filter is simulated with SPICE and it is found that predefined constraints are satisfied accurately. While steps 1 and 2 outlined above can be partially automated with existing mathematical software (Matlab, Mathematica, etc.) tools and computer-aided design (CAD) tools as SPICE and Cadence Spectre, performing step 3 for the generic case is impossible without simplifying assumptions and/or appropriate transformations applied to the raw transfer function H ( s ) in steps 1 and 2. For example, a fifth-order low pass filter can be implemented with, for example, a first-order filter and two second order filters, connected in series. Thus, any scheme to circumvent these issues must satisfy the following two conditions:
  • Eliminate all manual and/or time-consuming/error-prone calculation steps.
  • It must be possible to seamlessly verify that the final design satisfies specifications with a proven technique or tool.
The proposed scheme exploits the twin concepts of canonical ( or normalized or prototype ) filter and ladder networks in combination with predefined filter tables []. Ladder networks consist entirely of passive (resistor) and reactive (capacitor, inductor) and avoid the physical constraints (e.g., gain bandwidth product, slew rate, etc.) of active semiconductor-based devices, e.g., operational amplifier. Reactive components have a cutoff frequency (typically in the high MHz range); effective modifications have been developed to tackle this issue. The entire design process can be fully automated and is applicable to the entire frequency range from low (e.g., audio) to microwave (100s of MHz and 10s of GHz). Automation completely removes the manual error-prone step, and when used in combination, the popular circuit simulation tool, SPICE, performance characteristics can be evaluated and fine-tuned quickly. These topics are elaborated on in the subsequent chapters.
References
Matthaei, G. L., Young, L., & Jones, E. M. T. (1964). Microwave filters, impedance-matching networks, and coupling structures . New York: McGraw-Hill. LCCN 64-7937.
Zverev, A. I. Handbook of filter synthesis (Rev. Ed.). ISBN-13: 978-0471749424; ISBN-10: 0471749427.
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