Abstract:
A method of determining accurately and expeditiously the frequency of a coherent signal from an incoming electrical signal is disclosed. The method comprises the steps of: generating a time sequence of sampled data signals from the incoming electrical signal; detecting the coherent signal in the time sequence of sampled data signals and generating a frequency estimate thereof; and determining the frequency of the detected coherent signal based on a function of the frequency estimate and a time segment of sampled data signals associated with the coherent signal. A system for performing the same is also disclosed.

Description:
BACKGROUND OF THE INVENTION 
     The present invention is directed to the detection of coherent signals, in general, and more particularly, to a system and method of determining the frequency of a coherent signal detected from an incoming signal using a frequency estimate of the coherent signal to expedite the processing of a time segment of sampled data signals associated with the coherent signal. 
     In systems utilizing Doppler techniques for measuring parameters, such as a laser Doppler velocimeter (LDV) or a LIDAR, for example, coherent bursts of Doppler frequency shifted echo or return signals that are received intermittently and for brief durations are processed to measure each associated parameter. Not only is the detection of these coherent bursts from the incoming or received signal important, but an accurate and expeditious determination of the frequency of the detected burst is equally important. In an LDV or LIDAR system, for example, the signal frequency of the coherent burst is linearly proportional to a component of a velocity parameter being measured. This Doppler shifted frequency may range over several orders of magnitude approaching one gigahertz. Accordingly, the accurate and reliable frequency measurement of such coherent bursts with a low signal-to-noise ratio (SNR) is critical to accurate velocity measurements. 
     Because of the frequency ranges or bandwidths involved with such parameter measurements, real time signal processing of the coherent bursts is currently limited to crude frequency resolution. In general, a front end real time coherent burst detector, which may be of the type described in U.S. Pat. No. 4,973,969 or U.S. Pat. No. 5,289,391, for example, is coupled with a post-processor for processing the burst signals to obtain a high resolution frequency measurement. The coherent burst detector detects the coherent pulse in the incoming signal, collects data samples of the incoming signal over the time segment associated with the detected burst, and triggers the post-processor to process the collected data samples to determine the burst frequency. In order for the post-processor to determine the frequency of the burst accurately, it needs to process a large number of data samples with a commensurately sized spectral transform algorithm. However, speed of processing greatly diminishes as the size of the spectral transform increases to meet greater accuracy requirements creating longer processing times per burst. Accordingly, if a subsequent burst occurs during the processing of a burst, it may not be processed. 
     Currently, update rates for tracking the coherent bursts dictate the processing time allocated to process a burst signal to determine the frequency thereof at a specified accuracy or resolution. Therefore, update rates and accuracy requirements have a tendency to conflict with one another. That is, the processing time for each burst is set to ensure the processing of the bursts as they occur without loss of substantive burst information. As the update rate increases, the specified processing time decreases. On the other hand, the accuracy or resolution of the frequency measurement is not diminished. Accordingly, the post-processor has to maintain accuracy, but with a shorter processing time. Current coherent burst signal processing systems are unable to resolve this conflict. 
     Accordingly, what is desired is a system and method for measuring frequency of the coherent bursts at speeds and accuracy commensurate with the current and future demands of update rates and resolution. A processor that can process the sampled data of a coherent burst signal quickly and accurately will ensure that a minimum number of intermittent bursts are missed while waiting for the completion of a burst signal frequency measurement. 
     SUMMARY OF THE INVENTION 
     In accordance with one aspect of the present invention, a method of determining the frequency of a coherent signal from an incoming electrical signal comprises the steps of: generating a time sequence of sampled data signals from the incoming electrical signal; detecting the coherent signal in the time sequence of sampled data signals and generating a frequency estimate thereof; and determining the frequency of the detected coherent signal based on a function of the frequency estimate and a time segment of sampled data signals associated with the coherent signal. 
     In accordance with another aspect of the present invention, a system for determining the frequency of a coherent signal from an incoming electrical signal comprises: means for generating a time sequence of sampled data signals from the incoming electrical signal; means for detecting the coherent signal in the time sequence of sampled data signals and generating a frequency estimate thereof; and means for processing a time segment of the sampled data signals associated with the detected coherent signal and the generated frequency estimate to determine the frequency of the detected coherent signal. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram schematic of a coherent burst frequency measurement system suitable for embodying the principles of the present invention. 
     FIG. 2 is a time graph exemplifying a time segment portion of an incoming signal associated with a coherent burst signal. 
     FIG. 3 is a graph exemplifying a frequency spectrum of the time segment portion illustrated in FIG.  2 . 
     FIG. 4 is a time graph exemplifying a demodulated time segment associated with the coherent signal. 
     FIG. 5 is a graph exemplifying a frequency spectrum of the demodulated time segment illustrated in FIG.  4 . 
     FIG. 6 is a block diagram schematic of a coherent signal detector suitable for use in the embodiment of FIG.  1 . 
     FIG. 7 is a block diagram schematic of an alternate embodiment of a data buffer for use in the embodiment of FIG.  1 . 
     FIG. 8 is a block diagram schematic of a filter and downsampling function suitable for use in the embodiment of FIG.  1 . 
     FIG. 9 is an illustration of a curve fitting method for interpolating between frequency signals of a spectral transformation. 
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     FIG. 1 is a block diagram schematic of a coherent burst frequency measurement system  10  suitable for embodying the principles of the present invention. The system of FIG. 1, by way of example, may be part of a laser Doppler velocimeter (LDV) such as described in U.S. Pat. No. 4,818,101 or U.S. Pat. No. 5,272,513, for example, or part of continuous wave Doppler LIDAR such as described in the U.S. Pat. No. 5,164,784, for example. However, it is understood that the embodiment of FIG. 1 is not limited in application to such systems, but rather may be used in any system in which a received or incoming signal includes coherent burst signal having a frequency which is used in the measurement of a parameter. In the present embodiment, an incoming signal  12  is received by a coherent burst trigger circuit  14 . The incoming signal  12  may be a conditioned electrical signal converted from a front end optics receiver of a LDV or LIDAR, for example. Signal  12  may have been bandpass filtered to remove any low frequency signal components caused by the optics pedestal, for example, and any high frequency noise signal components. In the present embodiment, the incoming signal may range from substantially 12 to 188 MHz, for example. Also, by way of example, the coherent burst circuit  14  may be of the type described in the copending U.S. patent application bearing application Ser. No. 09/450,317, entitled “System and Method For Coherent Signal Detection Using Wavelet Functions”, and assigned to the same assignee as the instant application, which is hereby incorporated by reference in its entirety into the instant application. But, it is further understood that other coherent burst detector circuits, like those described in U.S. Pat. Nos. 4,973,969, 5,289,391 and 4,843,564, for example, may be used in the present embodiment without deviating from the principles of the present invention. 
     The coherent burst trigger or detection circuit  14  is depicted in greater detail in the block diagram schematic of FIG.  6 . Referring to FIG. 6, the incoming electrical signal  12  which includes coherent signal bursts intermittently and for short durations is sampled and digitized by the circuit  16  to provide a time sequence of digital data samples representative of the incoming electrical signal over signal line  18 . A clock signal  20  governs the sampling and digitization of circuit  16 . The present embodiment operates with a sampling rate of seven hundred and fifty (750) megahertz (MHz) to produce a time sequence of 750 million data samples of the incoming signal per second . In addition, the digitization may be a one-bit or multi-bit analog-to-digital conversion process depending on the particular application. While digitization is used because the downstream processing of the present embodiment includes digital processing circuitry, it is understood that the step of digitization may be omitted if suitable analog circuitry is embodied for the downstream processing of the data samples. The time sequence of data samples is buffered and conditioned in circuit  22  for downstream processing in a coherent signal detector circuit  24 . Circuit  22  may buffer the data samples to accommodate the slower processing rate of the circuit  24  and may further offer voltage signals compatible with the processor  24 . The clock signal  20  may also be conditioned and passed along to circuit  24  over signal line  26 . However, it is further understood that these steps may be also omitted depending upon the application and processing rate of the downstream circuitry. 
     The conditioned data samples are provided to the circuit  24  over a signal line  28  for processing therein and may be passed along over signal line  30  to a data buffer  32  which may be part of a post-processor circuit  34 , for example. In the present embodiment, the detector circuit  24  processes the data samples to generate frequency bins or ranges having collective energy levels. When the energy level of a frequency bin exceeds a predetermined reference level, the circuit  24  indicates the start of a coherent burst signal and when such energy level falls below the predetermined reference level, the end of the burst signal is indicated. The frequency bin or range triggering the burst signal indications is considered in the present embodiment as the estimate of the frequency of the detected coherent burst. Also, in the present embodiment, the conditioned clock signal may be passed along to the processor  34  over signal line  36  for processing synchronization and rate purposes. The start and stop detection indications of the coherent signal may be supplied to the processor  34  over a trigger signal line  38  along with the corresponding frequency estimate over a signal line  40  for further processing to measure an accurate frequency of the detected coherent burst signal. More specifically, circuit  24  may be a programmable gate array that is programmed to process the data samples using a Wavelet function, Fourier function or other spectral transformation algorithm to generate uniformly eight frequency bins over a frequency range of 12 to 188 MHz in which case, each frequency bin contains a frequency range of (188-12)/8 MHz. A digital code representing the frequency bin of the detected coherent signal is provided over signal line  40  as representing the frequency estimate. For a more detailed description of such an embodiment, reference is made to the above identified U.S. patent application Ser. No. 09/450,317. It is understood that the aforementioned number of frequency bins and frequency ranges thereof are merely described by way of example and that other frequency bins and ranges may be used for frequency estimates without deviating from the principles of the present invention. 
     In the present embodiment of FIG. 6, the processor  34  may be triggered by the start indication of line  38  to start storing data samples of the time sequence received over line  40  into the data buffer  32  and triggered to stop storing such data samples upon reception of a stop indication over signal line  38 . At the stop indication, the data buffer  32  will have stored therein a time segment of data samples associated with the current detected coherent signal which the processor  34  will process along with the corresponding frequency estimate of line  40  to determine the frequency of the detected coherent signal. Alternatively, as depicted by the block diagram schematic of FIG. 7, a data buffer  42 , which may be of the circular variety, stores continuously a time segment of the time sequence of data samples in a sliding time window fashion. When the processor  34  receives the stop indication over line  38  or some other similar indication, it loads a secondary data buffer  44  with the immediate time segment contents of the buffer  42 . This data loading of the secondary buffer may take place at such a rate so as to not interfere with the data sample collection of buffer  42  which continues to store data samples of the incoming signal in the time sequence. Both or one or the other of the data buffers  42  and  44  may be part of the processor  34  or be a separate unit therefrom without deviating from the principles of the present invention. 
     Reference is made back to the schematic of FIG. 1 for a description of the processing functions of the processor  34  which may be, for the purposes of the present embodiment, an integrated circuit digital signal processor of the type manufactured by Texas Instrument bearing model number TMS320C6201, for example. The coded frequency estimate signal  40  is received by the processor  34  and processed by a functional block  50  which may operate to generate a modulation frequency signal  52  governed by the clock rate  36  (not shown). The data samples of the time segment associated with the detected coherent signal being stored in the circular buffer  32  are retrieved therefrom over line  56  for demodulation by the modulation frequency signal  52  in the functional block  54  governed by the clock rate  36 . The modulation frequency is representative of the coded frequency estimate of the detected coherent signal. In the present embodiment, the modulation frequency f c  is chosen to be substantially the center frequency of the range of frequencies of the frequency estimate having a complex demodulation function d(t) as follows: 
     
       
           d ( t )=cos(2 πf   c   t )+ i  sin(2 πf   c   t ).  Eq. 1 
       
     
     Thus, demodulating the data samples of the time segment of the incoming signal retrieved from the data buffer  32  results in the demodulation signal S d  (t) according to the following expression: 
     
       
           S   d ( t )= S   0 ( t )× d ( t ),  Eq. 2 
       
     
     where S 0 (t) is the time signal represented by the sampled data signal of the time segment, and S d (t) is a complex signal. It is understood that a frequency other than the center frequency or even a composite of frequencies may be used to represent the frequency estimate without deviating from the principles of the present invention. 
     By way of example, the time graph of FIG. 2 illustrates a time segment of the incoming signal associated with the detected coherent signal and FIG. 3 represents the spectral make up thereof with substantial energy levels at the points 25 MHz and 100 MHz. Suppose for the present example, the frequency bin of the frequency estimate had a center frequency of approximately 80 MHz, then the time signal of FIG. 2 is modulated with a modulation frequency signal of 80 MHz to yield a complex modulation signal which may exhibit the characteristics of the real waveform exemplified in FIG.  4  and which has a spectral make up shown by the frequency spectrum of FIG.  5 . Note that in the spectrum of FIG. 5, 80 MHz is transformed or shifted to baseband or zero frequency and the frequency spectrum surrounding 80 MHz in FIG. 3 is centered about baseband in FIG.  5 . Accordingly, the energy peak at 100 MHz of the time segment is transformed to −20 MHz in the demodulation signal. In addition to the aforementioned frequency shift, the spectrum of the demodulated signal depicted in FIG. 3 is also rotated 180° about the frequency f c  shown by the dashed vertical line in FIG.  3 . Accordingly, the graph of FIG. 5 depicts the results of the 180° rotation about the dashed line and the shifting of the dashed line to baseband or zero frequency. Now that frequency of the peak energy of interest is closer to zero frequency, i.e. −20 MHz, a much lower Nyquist frequency may be used to resolve the frequency associated with this peak. 
     Next, the demodulation signal  57  is low pass filtered and downsampled in the functional block  58 . Reference is made to the block diagram schematic of FIG. 8 for a more detailed description of the functions of block  58 . Referring to FIG. 8, a low pass filtering of the demodulation signal  57  is performed in block  60  wherein all of the higher frequency components, both positive and negative, of the complex demodulation signal  57  are discarded to prevent the occurrence of anti-aliasing among other effects. Without the low pass filter, energy of the higher frequency content may show in the downsampling processing and have an affect on the resulting frequency determination. In the present embodiment, the cut-off frequency of the low pass filter is based on the frequency estimate. For example, the frequency range of the estimate may become the range of the low pass filter. In other words, the center frequency and frequency range of the frequency estimate may be used as the modulation frequency and low pass filter cut off frequency, respectively. Any conventional sliding average digital filter algorithm may be used to embody the low pass filter function. For the present embodiment, a suitable digital filter algorithm comprises the COMB filter. In block  62 , a downsampling of the filtered signal is performed wherein the circuit keeps or passes for processing only one of N filtered complex data samples from block  60 . For the present example, N is chosen to be  16 , i.e. the block  62  passes only every 1 of 16 real and imaginary data samples for further processing. 
     Note that if the time segment data buffer  32  started with 4096 data samples, with the downsampling of 1 of 16, only 256 data samples would be passed for further processing. Next, in block  64 , a time-series window function may be applied to the data samples passed by the downsampler  62  to reduce any spectral leakage of the transformed data. A suitable function for these purposes is a Hanning time-series window. Once the filtering and downsampling of block  58  are performed, a spectral transformation of the remaining data samples is conducted in a functional block  66  to generate a spectrum of frequency signals within the narrow bandwidth of the low pass filter. The spectral transformation may be of a size commensurate with the number of remaining data samples, i.e. if the remaining data samples is 256, then a 256 point spectral transformation would be performed in block  66 . Again, any discrete spectral transformation, like a Fourier or Wavelet function algorithm, for example, is considered suitable for the present embodiment. For this example, a 256 point Fast Fourier transform (FFT) algorithm is used to perform the spectral transformation yielding 256 frequency components from the 256 data samples provided by block  62 . Since the transformation is complex, all 256 frequency components centered about the baseband will be unique. The frequency of the detected coherent signal may then be determined from results of the spectral transformation. 
     In the present embodiment, the peak or maximum spectral magnitude of the spectral transformation may be determined and used for determining the coherent signal frequency in block  68 . Alternatively, some curve fitting algorithm could be used to improve resolution by interpolating between the discrete frequency points of the spectral transformation such as that shown in the graphical illustration of FIG.  9 . Referring to FIG. 9, suppose that frequency points f 1 , f 2 , and f 3  are exemplary spectral transformation frequencies with respectively corresponding magnitudes M 1 , M 2  and M 3 , then a suitable curve for fitting the magnitudes is shown by the dashed line  70 . A peak or maximum magnitude M p  of the curve  70  provides for the frequency f p  which lies between the frequency points f 1 , and f 2 , thus providing improved resolution in the frequency determination process. Such curve fitting may be accomplished by a second order polynomial expression, a spline or other similar expression, for example. Thereafter, the original peak frequency f p  is recovered from the demodulated peak frequency f d  and used as a measure of the frequency of the coherent signal using the following expression: 
     
       
           f   p   =f   c   =f   d ,  Eq. 3 
       
     
     where f c  is the modulation frequency determined from the frequency estimate. 
     In summary, the foregoing described embodiment provides a unique system and method for determining the frequency of a coherent signal detected from an incoming signal with both accuracy and speed. A time segment of data samples of the incoming signal associated with a detected coherent burst signal is demodulated with a frequency modulation signal representative of a frequency estimate of the coherent signal to shift the frequency spectrum of the time segment to lower frequencies which may be centered about baseband or zero frequency. The data samples of the complex demodulated time segment are low pass filtered and downsampled to remove undesirable higher-frequency components and to reduce the sampling rate and spectral transform size. The cut-off frequency of the low pass filter may be based on the frequency range of the estimate. Accordingly, a relatively smaller and consequently, faster discrete spectral transform is applied to the remaining samples to yield a spectrum of discrete frequency signals commensurate with the number of data samples being transformed. A frequency corresponding to the maximum spectral magnitude of the transformation is converted back to the original frequency domain based on the modulation frequency and used a measure of the coherent signal frequency. Curve fitting may be used to interpolate between the discrete frequencies of the spectral transformation to improve the resolution of the frequency determination. 
     While the present invention has been described herein above in connection with one or more embodiments, it is understood that it should not be limited in any way, shape or form to any specific embodiment but rather construed in broad scope and breadth in accordance with the recitation of the set of claims appended hereto.