Electrical computers: arithmetic processing and calculating – Electrical digital calculating computer – Particular function performed
Reexamination Certificate
2002-02-27
2004-03-02
Malzahn, David H. (Department: 2124)
Electrical computers: arithmetic processing and calculating
Electrical digital calculating computer
Particular function performed
Reexamination Certificate
active
06701335
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention is directed to a digital signal processing (DSP) system having a digital frequency response compensator and an arbitrary response generator. More generally, the present invention relates to systems having an analog input signal, analog electronics (e.g. attenuators, gain elements, and buffers), and an analog-to-digital converter (ADC) for converting the analog input signal into a sequence of numbers that is a digital representation of the input signal. This invention pertains to instruments designed with the aforementioned components in order to acquire waveforms for the purpose of viewing, analysis, test and verification, and assorted other purposes. More specifically, this invention pertains to digital sampling oscilloscopes (DSOs), especially ultra-high bandwidth and sample rate DSOs and single-shot DSOs (sometimes referred to as real-time DSOs). These DSOs are capable of digitizing a voltage waveform with a sufficient degree of over-sampling and fidelity to capture the waveform with a single trigger event.
Traditionally, DSOs have been the primary viewing tool for engineers to examine signals. With the high-speed, complex waveforms utilized in today's communications and data storage industries, the simple viewing of wave forms has been de-emphasized and greater demand has been placed on DSOs that are also capable of analyzing the waveforms. This increased desire for DSO analysis capability requires a greater degree of signal fidelity (i.e. a higher quality digitized waveform). While greater demands for signal fidelity are being made, the desire for DSOs having higher bandwidth and sample rates similarly continues unabated. Unfortunately, a high-speed signal requires a high-bandwidth DSO, and a premium is paid for ultra-high bandwidth, high sample rate, real-time DSOs.
Sampling rates for digital oscilloscopes have been doubling approximately every 2-2½ years, with bandwidth doubling almost every 4 years. This increase in bandwidth has not come without a price. Often, analog components are stretched to their limits. Sometimes, peaking networks are used to stretch the bandwidth even further. This push for higher bandwidth often comes at the price of signal fidelity, specifically in the areas of pulse response (overshoot and ringing) and frequency response flatness. This is because peaking tends to be somewhat uncontrolled (i.e. it is difficult to peak-up a system while simultaneously maintaining a flat response). Further, since the analog components are stressed to their bandwidth limits, the frequency response often drops precipitously if the bandwidth is exceeded. Hence, high-bandwidth oscilloscopes no longer have gentle frequency response roll-off characteristics.
Despite this situation, DSO customer's baseline expectations have not changed. Customers still expect low-noise—even though noise increases by a factor of the square root of two for every doubling of the bandwidth—and they expect DSOs to have a certain roll-off characteristic.
Further complicating the situation is the fact that the design of high-speed DSOs involves a tremendous amount of trade-off and compromise. The three main traditional metrics of signal fidelity—noise, frequency response, and time-domain response—all compete against one another. As mentioned previously, pushing higher bandwidths through an oscilloscope increases the noise in the output signal. Any variation from the single-pole or double-pole frequency response characteristics increases the overshoot and ringing. Pushing the bandwidth of the hardware components to their limits only makes the problem worse. Flattening the frequency response can worsen the pulse response. Improving the pulse response typically means reducing the bandwidth of the instrument (which is always undesirable). Because the DSO is a general-purpose instrument, the tradeoffs are chosen carefully but many customers are invariably unsatisfied. The only choice left to the user is between a few fixed bandwidth limits, which connect in a simple RC network. Even in bandwidth-limited modes, the response is often still not perfectly compliant with the single-pole response and can vary by up to 0.5 dB.
Compliance to a specified response is essential in the development of vertical market applications for a DSO where the scope emulates, for example, particular communication or disk-drive channels. The capability to emulate channels provides a rapid prototyping and analysis capability.
SUMMARY OF THE INVENTION
Therefore, in accordance with the present invention, a component capable of compensating for degradation due to increased bandwidth is provided (i.e. frequency response flatness and/or compliance to a particular desired response characteristic).
Further in accordance with the present invention, an adjustable component capable of making trade-offs with regard to noise, flatness and/or pulse response characteristics, rather than relying on static instrument characteristics is provided. The adjustable component thereby allows the instrument to be optimized for a given measurement.
In accordance with the present invention, a capability using the adjustable component to feedback the response characteristics of the instrument to the user is provided.
Still further in accordance with the present invention, a component capable of being calibrated for changing channel response characteristics is provided.
A preferred embodiment of the invention provides a signal processing system capable of compensating for a channel response characteristic of an input waveform. The system comprises input specifications, a filter builder, and a filter. The input specifications are used to specify the design of the filter and include channel response characteristics defining the response characteristics of a channel used to acquire the input waveform, and user specifications for specifying a desired frequency response and a degree of compliance to the desired frequency response. The filter builder generates coefficients for the filter and outputs final performance specifications. The filter has a compensation filter generator for generating coefficients corresponding to a compensation response on the basis of the inverse of the channel response characteristics, and a response filter generator for generating coefficients corresponding to a combination of an ideal response and a noise reduction response on the basis of the user specifications. The filter filters the input waveform and outputs an overall response waveform having a desired frequency response. The filter is comprised of a filter coefficient cache for storing the coefficients generated by the filter builder, a compensation filter portion for filtering the input waveform in accordance with the coefficients stored in the filter coefficient cache corresponding to the compensation response, and a response filter portion having a response filter stage and a noise reduction stage for filtering the compensated waveform output from said compensation filter portion that outputs the overall response waveform. The response filter portion filters using the coefficients stored in the filter coefficient cache corresponding to the combination of the ideal response and the noise reduction response.
In another aspect of the invention, the filter may be implemented as an infinite impulse response (IIR) filter or a finite impulse response (FIR) filter.
In a further aspect of the invention, the channel response characteristics may be predetermined based on a reference signal and the reference signal as acquired by the channel.
In still another aspect of the invention, the user specifications may comprise a bandwidth, a response optimization, a compensation compliance, and a filter implementation type. The response optimization may be a pulse response optimization implemented using a Besselworth filter, a noise performance optimization implemented using a Butterworth filter, or a flatness optimization implemented using a Butterworth filter. The filter implementation type may be finite impulse re
Frommer William S.
Frommer & Lawrence & Haug LLP
Kessler Gordon M.
LeCroy Corporation
Malzahn David H.
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