Coded data generation or conversion – Analog to or from digital conversion – Multiplex
Reexamination Certificate
2000-12-04
2002-03-26
Wamsley, Patrick (Department: 2819)
Coded data generation or conversion
Analog to or from digital conversion
Multiplex
C341S061000
Reexamination Certificate
active
06362760
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to a method and apparatus for acquiring wide-band random and pseudorandom noise encoded waveforms and specifically to a method and apparatus for acquiring wide-band signals, including deterministic signals, random signals and pseudorandom noise encoded waveforms that divides the waveform into a plurality of subbands prior to signal processing thereof.
BACKGROUND
Analog-to-digital converters are devices that convert real world analog signals into a digital representation or code which a computer can thereafter analyze and manipulate. Analog signals represent information by means of continuously variable physical quantities while digital signals represent information by means of differing discrete physical property states. Converters divide the full range of the analog signal into a finite number of levels, called quantization levels, and assigns to each level a digital code. The total number of quantization levels used by the converter is an indication of its fidelity and is measured in terms of bits. For example, an 8-bit converter uses 2
8
or 256 levels, while a 16-bit converter uses 2
16
or 65536 levels.
During the conversion process, the converter determines the quantization level that is closest to the amplitude of the analog signal at that time and outputs the digital code that represents the selected quantization level. The rate at which the output is created indicates the speed of the converter and is measured in terms of samples per second (sps) or frequency in Hertz (Hz). As will be appreciated, a larger number of bits and therefore quantization levels equates into a finer representation of the analog signal.
In designing an analog-to-digital converter, there are a number of considerations. In many applications for example it is desirable that the converter has not only a high rate of speed but also a large number of quantization levels or a high degree of fidelity. Such converters are difficult to build and therefore tend to be highly complex and very expensive. The key reason is that conversion errors and the consequential device layout constraints for reducing such errors, both of which can be ignored at slow speeds, can become significant at high speeds. As a result, in existing converters, high fidelity and high speed are commonly mutually exclusive; that is, the higher the converter speed the lower the converter fidelity and vice versa.
SUMMARY OF THE INVENTION
It is an object of the present invention to provide an analog-to-digital converter that has a high fidelity and a high speed. Related objectives are to provide such an analog-to-digital converter that is relatively simple and inexpensive.
The present invention is directed to a method and apparatus for processing signals, particularly wide-band signals, including deterministic signals, random signals, and signals defined by pseudorandom waveforms with a relatively high degree of fidelity and efficiency at a high speed and at a low cost. The invention is particularly useful for processing wideband signal, including signals defined by broadband signals (i.e., signals having a bandwidth of preferably more than about 1 kHz and more preferably more than about 1 GHz).
The signal can be in any suitable form such as electromagnetic radiation, acoustic, electrical and optical.
In one embodiment, the method includes the following steps:
(a) decomposing the analog or digital signal into a plurality of signal segments (i.e., subband signals), each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
(b) processing each of the signal segments to form a plurality of processed signal segments; and
(c) combining the processed signal segments into a composite signal that is digital when the signal is analog and analog when the signal is digital. As will be appreciated, the sum of the plurality of signal bandwidths is approximately equivalent to the signal bandwidth. The means for processing the signal segments can include any number of operations, including filtering, analog-to-digital or digital-to-analog conversion, signal modulation and/or demodulation, object tracking, RAKE processing, beam forming, null steering, correlation, interference-suppression and matched subspace filtering.
In a particularly preferred application, the signal processing step (b) includes either analog-to-digital or digital-to-analog conversions. The use of signal segments rather than the entire signal for such conversions permits the use of a lower sampling rate to retain substantially all of the information present in the source signal. According to the Bandpass Sampling Theorem, the sampling frequency of the source signal should be at least twice the bandwidth of the source signal to maintain a high fidelity. The ability to use a lower sampling frequency for each of the signal segments while maintaining a high fidelity permits the use of a converter for each signal segment that is operating at a relatively slow rate. Accordingly, a plurality of relatively inexpensive and simple converters operating at relatively slow rates can be utilized to achieve the same rate of conversion as a single relatively high speed converter converting the entire signal with little, if any, compromise in fidelity.
The means for decomposing the signal into a number of signal segments and the means for combining the processed signal segments to form the composite signal can include any number of suitable signal decomposing or combining devices (e.g., filters, analog circuitry, computer software, digital circuitry and optical filters). Preferably, a plurality or bank of analog or digital analysis filters is used to perform signal decomposition and a plurality or bank of analog or digital synthesis filters is used to perform signal reconstruction. The analysis and synthesis filters can be implemented in any number of ways depending upon the type of signal to be filtered. Filtration can be by, for example, analog, digital, acoustic, and optical filtering methods. By way of example, the filters can be designed as simple delays or very sophisticated filters with complex amplitude and phase responses.
In a preferred configuration, a plurality or bank of analysis and/or synthesis filters, preferably designed for perfect reconstruction, is used to process the signal segments. As will be appreciated perfect reconstruction occurs when the composite signal, or output of the synthesis filter bank, is simply a delayed version of the source signal.
In one configuration, the analysis filters and synthesis filters are represented in a special form known as the Polyphase representation. In this form, Noble identities are can be used to losslessly move the decimators to the left of the analysis filters and the interpolators to the right of the synthesis filters.
In another configuration, noise components in each of the signal segments can be removed prior to signal analysis or conversion in the processing step. The removal of noise prior to analog-to-digital conversion can provide significant additional reductions in computational requirements.
In yet another configuration, a coded signal is acquired rapidly using the above-referenced invention. In the processing step, the signal segments are correlated with a corresponding plurality of replicated signals to provide a corresponding plurality of correlation functions defining a plurality of peaks; an amplitude, time delay, and phase delay are determined for at least a portion of the plurality of peaks; and at least a portion of the signal defined by the signal segments is realigned and scaled based on one or more of the amplitude, time delay, and phase delay for each of the plurality of peaks.
In another embodiment, a method is provided for reducing noise in a signal expressed by a random or pseudorandom waveform. The method includes the steps of decomposing the signal into a plurality of signal segments and removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments. The
Kober Wolfgang
Thomas John K.
Data Fusion Corporation
Sheridan & Ross P.C.
Wamsley Patrick
LandOfFree
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