Patent Publication Number: US-7590177-B2

Title: Method and system for receiving pulse width keyed signals

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
   This application is a continuation of U.S. Non-Provisional Application Ser. No. 10/856,936, filed Jun. 1, 2004, now U.S. Pat. No. 7,295,607, issue date Nov. 13, 2007, which claims benefit to U.S. Provisional Application No. 60/568,856, filed May 7, 2004, all of which are incorporated herein in its entirety by reference. 

   BACKGROUND OF THE INVENTION 
   1. Field of the Invention 
   The present invention relates to the field pulse width keying. In particular, the present invention relate to the field of determining pulse related characteristics of pulse width keyed signals. 
   2. Related Art 
   Pulse width keying uses the length of a pulse over a time period for bit representation. In some modulation schemes, for example, a bit “0” is represented as a 1.0 millisecond (ms) pulse followed by 0.5 ms blanking time. In these schemes, a bit “1” might be represented as a 0.5 ms pulse followed by 1.0 ms blanking time. 
   In practice, pulse width keyed signals are used in a variety of applications. Included in these applications is the field of modern radar and radar receivers. Radars use pulse width keyed signals, for example, to determine target range, speed, and angle data. Radar receivers, such as radar warning receivers used in military applications, can discriminate between different radars, and different types of radars, on the basis of the pulse related characteristics of their respective pulse keyed signals. 
   A major shortcoming of using pulse width keyed signals, however, is the ability of the receiving system to accurately measure pulse data in noisy environments. Many conventional receiving systems, for example, rely purely upon envelope and amplitude threshold detection techniques to measure characteristics, such as pulse widths. In noisy environments, however, it becomes difficult to distinguish actual pulse related data from noise, using the conventional threshold detection techniques. 
   What is needed, therefore, is a more robust technique to detect and measure pulse related characteristics, such as pulse widths, associated with pulse width keyed signals. 
   BRIEF SUMMARY OF THE INVENTION 
   Consistent with the principles of the present invention as embodied and broadly described herein, a method to process a pulse width keyed signal includes digitizing a received pulse width keyed signal and transforming the digitized signal to at least one of power domain and absolute value domain. The converting produces a converted signal. The method also includes estimating a signal power of the converted signal in a wide band filter to produce data representative of a first signal having first type signal shape properties and estimating a signal power of the converted signal in a narrow band filter to produce data representative of a second signal having second type signal shape properties. Finally, the first and second type data are compared to produce information representative of pulse related characteristics of the received signal. 
   Further embodiments, features, and advantages of the present invention, as well as the structure and operation of the various embodiments of the present invention are described in detail below with reference to the accompanying drawings. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES 
     The accompanying drawings, which are incorporated in and constitute part of the specification, illustrate embodiments of the present invention and, together with the general description given above and the detailed description of the embodiments given below, serve to explain the principles of the invention. In the drawings: 
       FIG. 1A  is a block diagram of a receiving system constructed in accordance with an embodiment of the present invention; 
       FIG. 1B  is a more detailed block diagram of the pre-processing system shown in  FIG. 1A ; 
       FIG. 2  is a diagram of exemplary signal waveforms outputs from the pre-processing system shown in  FIG. 1B ; 
       FIG. 3  is a block diagram of the path I processing system shown in  FIG. 1A ; 
       FIG. 4  is a block diagram of the path II processing system shown in  FIG. 1A ; and 
       FIG. 5  is a flow diagram of an exemplary method of practicing an embodiment of the present invention. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   The following detailed description of the present invention refers to the accompanying drawings that illustrate exemplary embodiments consistent with this invention. Other embodiments are possible, and modifications may be made to the embodiments within the spirit and scope of the invention. Therefore, the detailed description is not meant to limit the invention. Rather, the scope of the invention is defined by the appended claims. 
   It would be apparent to one of skill in the art that the present invention, as described below, may be implemented in many different embodiments of software, hardware, firmware, and/or the entities illustrated in the figures. Any actual software code with the specialized control of hardware to implement the present invention is not limiting of the present invention. Thus, the operational behavior of the present invention will be described with the understanding that modifications and variations of the embodiments are possible, given the level of detail presented herein. 
     FIG. 1A  is a block diagram of a receiving system  100  constructed in accordance with an embodiment of the present invention. The receiving system  100  is a new receiver architecture that uses power detection for robust pulse width measurements in the presence of noise. Two different implementations of the architecture are provided and can be used in combination to further enhance the performance of the receiving system  100 . 
   In  FIG. 1A , the receiving system  100  includes a pre-processing system  101  configured to produce a number of waveform data signals as an output. One of the waveform data signals is provided as an input is provided as an input to a path I processing system  130  (discussed in greater detail below) where pulse related measurements are performed. Other waveform data signals are provided to a path II processing system  132  (also discussed in greater detail below), where separate pulse related measurements are performed. 
     FIG. 1B  is a block diagram of the pre-processing section  101  of the receiving system  100 , shown in  FIG. 1A . In  FIG. 1B , the pre-processing system  101  includes an analog to digital converter (ADC)  102 . The ADC  102  is configured to receive an input analog signal SIG input  and convert it to digital domain. A source of the input analog signal SIG input  could be a radar system that uses pulse width keyed signals. The ADC  102  receives the input analog signal SIG input  at one input port and receives a sampling signal (fs) at another input port. The sampling signal (fs) is used to sample the input signal SIG input  at a predetermined sampling rate. Although any suitable sampling frequency can be used, the sampling signal (fs) in the present invention has a frequency of about one mega-hertz. A resulting digital signal is then output from the ADC  102 . 
   The digital signal output from the ADC  102  is then converted to power domain within a power converter  104 . The power converter  104  converts to power domain by taking the square of signal level data that represents the signal output from the ADC  102 . Simultaneously, the output digital signal is converted to an absolute value domain within an absolute value converter  106 . Outputs of the power converter  104  and the absolute value converter  106  are provided to a multiplexer  108 . 
   The multiplexer  108 , which can be configured via hardware and/or software using an input select switch  110 , selects between outputs from the power converter  104  and the absolute value converter  106 . Converting the signal to the power domain conversion provides a more reliable signal energy expression and preserves more of the signal&#39;s energy than the absolute value domain conversion. The power converter  104 , however, is more expensive to implement. The absolute value domain conversion provides slightly inferior signal expression, but is cheaper to implement. As a matter of practice, the multiplexer  108  is typically configured to select the output from the power converter  104 , since it is more reliable. The output of the absolute value converter  106  is most serves as a back up (e.g., purposes of verification). The output of the multiplexer  108  is then provided to filters  112  and  114 . 
   The filters  112  and  114  are low pass filters and are provided for estimating signal power. While each of the filters  112  and  114  can be implemented using a number of different architectures, in the embodiment of  FIG. 1 , the filters  112  and  114  are cascaded integrated comb (CIC) filters. The filter  112  has wide bandwidth properties and the filter  114  has narrow bandwidth properties. 
   In the present invention, the output of the multiplexer  108  includes digital samples representative of the power domain or the absolute value domain of the input signal SIG input . The CIC filters  112  and  114  perform moving average filtering of the digital samples output from the multiplexer  108 . 
   For example, the wide bandwidth CIC filter  112  averages the digital samples using predetermined integration time periods and sample increments. In  FIG. 1B , the integrations time period of the CIC filter  112  was programmed to be within a range of 8 to 256 microseconds. A programmable sliding window operation is also used, sliding in exemplary increments of 8 samples. The integration times and sliding increment are programmable. Thus, the present invention is not limited to any particular integration and/or increment value(s). 
   The narrow bandwidth CIC filter  114  has been programmed to an integration time period of 256 to 512 microseconds, using the same sliding window of 8 sample increments. 
   As noted above, the filter  112  is implemented as a wide bandwidth filter. As such, its time span is inversely proportional to its bandwidth. The wider the bandwidth of the filter, the shorter (faster) its time span. This concept applies equally to the filter  114 , implemented as a narrow bandwidth filter. That is, the more narrow the bandwidth, the longer (slower) its time span. 
   A shorter time span enables the system  100  to respond more accurately to very rapid changes in the energy level of an input signal. However, an issue with using the wideband filter  112  by itself is that when the signal&#39;s energy quickly increases due to the rising edge of a received pulse, a portion of this increased energy may be due to noise. Thus, in a noisy environment, the signal&#39;s energy within the wideband (fast response) filter  112  may be constantly going up and down, rapidly increasing and then rapidly decreasing. Therefore, the operation of the wideband filter  112  is complimented by operation of the narrowband (slow response) filter  114 . 
   The narrow band filter  114  is slower to react to changes in a signal&#39;s energy and is therefore somewhat more stable. When signal energy is received, the filter  114  reacts gradually and is therefore less susceptible; for example, to noise spikes tend to be of shorter duration. The output of the narrowband filter  114 , therefore, is somewhat cleaner than the output of the wideband filter  112 . 
   Thus, as shown in  FIG. 1B , the present invention integrates the use of two different bandwidth filters, such as the wide bandwidth filter  112  and the narrow bandwidth filter  114 . The use of two different bandwidth filters provides more robust and reliable signal power estimation and, consequently, more accurate pulse width measurements. 
   Outputs of the wideband filter  112  and the narrowband filter  114  are provided as inputs to optional down samplers  116  and  118 , respectively. Down sampling decreases the timing resolution of the output waveforms. The down samplers  116  and  118 , however, can be omitted (e.g., for cost savings) without impacting the operation of the present invention. Although a down sampling factor of 8 is illustrated in  FIG. 1B , any suitable down sampling factor can be used. Generally, the higher the down sampling factor, the lower the timing resolution of the associated signal. 
   The wideband filter  112 , by way of the optional down sampler  116 , forms an output numerical value  120 , representative of a quantized waveform SIG A . The narrowband filter  114 , by way of the optional down sampler  118 , forms an output numerical value  122 , representative of a quantized waveform SIG B . A combiner  124  subtracts the numerical values  120  and  122  to form a numerical value  126 , which is representative of a quantized waveform SIG C . 
     FIG. 2  provides an illustration of exemplary waveform signal shapes associated with the receiving system  100 . For example,  FIG. 2  depicts the input signal SIG input . The signal SIG input  includes a pulse (P) that might be representative, for example, of radar target data (range, rate, etc.). On the other hand, the pulse (P) could be pure noise. Also shown in  FIG. 2 , are each of the exemplary waveforms SIG A , SIG B , and SIG C . The waveform SIG A  is the output of the wide bandwidth (fast response) filter  112  and resembles a relatively sharp square wave. More specifically, edges of the waveform SIG A  rise and fall relatively quickly. The waveform SIG B , output from the narrow bandwidth (slow response) filter  114 , is somewhat similar. However, rising and falling edges of the waveform SIG B  are more gradual than those of the waveform SIG A . 
   The waveform SIG C  is formed from taking the difference between the waveforms SIG A  and SIG B  within the combiner  124  of  FIG. 1B . As shown in  FIG. 2 , the waveform SIG C  includes a peak  200  and a dip  202 . When the signal SIG C  reaches the peak  200 , it begins to fall, eventually reaching an amplitude value of zero. The signal SIG C  remains at this zero value until the pulse (P) begins to disappear, forming its falling edge represented by the dip  202 . 
   The pre-processing system  101  receives and processes the input signal SIG input . Among other things, the pre-processing system  101  integrates the use of the two different bandwidth filters  112  and  114  to form the waveforms SIG A , SIG B , and SIG C . Each of these waveforms includes its own unique data that can then be used by one or more of the processing systems  130  and  132  to accurately determine pulse related characteristics of the input signal SIG input , such as pulse width. For example, as shown in  FIG. 2 , each of the waveforms SIG A , SIG B , and SIG C  conveys unique rising edge and falling edge information related to the pulse (P). This rising edge and falling edge information is later used as a basis for accurately measuring the width (W P ) of the pulse (P). 
   The waveform SIG C  is provided as an input to the path I processing system  130 . The waveforms SIG A  and SIG B  are simultaneously provided as inputs to the path II processing system  132 . Although the processing systems  130  and  132  are depicted in  FIG. 1A  as operating in a complimentary arrangement, each can be used to as a separate and independent technique to determine the pulse width (W P ). In the complimentary arrangement, outputs of the processing systems  130  and  132  can be compared and/or averaged to further enhance the reliability and accuracy of pulse width (W P ) determinations made by the system  100 . 
   As shown in  FIG. 3 , the path I processing system  130  includes a low pass filter  302  and a peak/dip detector  304 . The low pass filter  302  provides one additional level of filtering via a moving average calculation to remove any remaining noise components from the waveform SIG C . In the embodiment of  FIG. 3 , the low pass filter  302  calculates the moving average in accordance with a well know exponential windowing function α/[(1+(α−1) z −1 ]. The present invention, however, is not limited to this approach. An output of the filter  302  is provided as an input to the peak/dip detector  304 . 
   As illustrated in  FIG. 2 , the waveform SIG C  includes unique rising edge and falling edge information related to the pulse (P) of the input signal SIG input . For example, the peak  200  and the dip  202  are formed within the waveform SIG C  and reliably represent the location of the rising and falling edges of the pulse (P). The peak/dip detector  304  first senses the presence of the peak  200  and the dip  202 , it then records the time that the peak  200  occurs, and finally records the time that the dip  202  occurs. 
   The recorded time of the peak  200  is a first assessment of the system  100  (i.e., based upon the waveform SIG C ) of the actual time of arrival (TOA) of the pulse (P). Correspondingly, the recorded time of the dip  202  is a first assessment of the time of ending (TOE) of the pulse (P). The width (W P ) of the pulse (P) is represented by a difference between the TOA and the TOE. The width (W P ), obtained by analyzing the signal SIG C , is output from the peak/dip detector  304  in the form of a single TOA/TOE value  306 . 
   In  FIG. 3 , the peak/dip detector  304  includes a state machine, although the present invention is not limited to this approach. Within the peak/dip detector  304 , a preliminary TOA/TOE determination is made and is then compared with a TOA/TOE value  308  as a confirmation check. The TOA/TOE value  308  can be provided using the conventional threshold techniques noted above. This comparison results in the TOA/TOE value  306 . Simulation results have shown that the techniques of the path I processing system  130  provide significant improvements in the reliability of pulse width measurements in comparison to the conventional threshold techniques noted above. 
     FIG. 4  provides a more detailed illustration of the path II processing system  132 . As previously discussed, the path II processing system  132  represents an alternative, or complimentary, approach for determining the width (W P ) of the pulse (P). In general, the processing system  132  more carefully determines power (S) and noise (N) characteristics of the waveforms SIG A  and SIG B . These power (S) and noise (N) determinations are then used to provide more robust threshold techniques to determine the TOA and TOE of the pulse (P). 
   In the processing system  132 , the waveform SIG B  is simultaneously provided as an input to a noise estimator  400  and a threshold detection circuit  401 . Also occurring simultaneously with the inputs of the SIG B , the signal SIG A  is input to a threshold detector  402 . 
   The noise estimator  400  is provided to calculate a noise floor of the signal SIG B , and includes a delay module  403  and a low pass filter  404 . The delay module  403  delays the input signal SIG B  in accordance with a well-known inverse delay expression (Z −N ). The delay of the signal SIG B  provides sufficient time for the system to detect the presence of a pulse and stop the noise floor estimation. A delayed signal SIG B  is then provided as an input to the low pass filter  404 . The low pass filter  404  performs a moving average calculation to reliably estimate the noise (N) of the signal SIG B . 
   By way of background, when the pulse in the signal SIG B  appears at the input to the low pass filter  404 , it includes both power (S) and noise (N) components. Thus, the signal SIG B  can be expressed as (S)+(N), where (N) is equivalent the energy amplitude at the input of the filter  404  when there is no signal present. On the other hand, when there is noise only, and the signal SIG B  appears at the input to the low pass filter  404 , it includes only the noise (N) component. The noise floor estimation block should be turned on only when there is no pulse presented. The resulting noise (N) component, now updated via the moving average, becomes the noise floor estimate of delayed signal SIG B . The actual output of the noise estimator  400 , therefore, is a numerical noise floor value (NFV)  406 , representative of the noise floor estimate of the signal SIG B . Though not a requirement of the instant invention, the low pass filter  404  is implemented in the same manner as the low pass filter  302  of  FIG. 3 . 
   In the processing system  132  of  FIG. 4 , the NFV  406  is provided as a first input to a combiner  408 , positioned along an input port  410  to a multiplexer  412 . The accurate estimate of the power (S) component, refined by the moving average calculation above, is provided as a second input to the combiner  408 . The NFV  406  (noise floor estimate) is then subtracted from the power (S) component to form an adaptive threshold value (T ADAP ) of the signal SIG B . 
   In the present invention, an operator can also program a preset threshold value (T PRESET ) using conventional techniques. The preset threshold value (T PRESET ) is then provided as another input to the multiplexer  412 , along an input port  414 . As an added programmability feature, the user can configures a switch  415  to select between the adaptive threshold value (T ADAP ) and the preset threshold value (T PRESET ). In practice, however, the adaptive threshold value (T ADAP ) is preferable since it is derived from the actual input signal SIG B . 
   The selected threshold value (T PRESET  or T ADAP ), output from the multiplexer  412 , is provided as additional input to each of the threshold detectors  401  and  402 . The selected value represents the threshold trigger of each of the detectors  401  and  402 . That is, the input signals SIG A  and SIG B  will only be output from the respective detectors  402  and  401  when their corresponding amplitudes exceed the selected threshold value (T PRESET  or T ADAP ). The threshold detectors  401  and  402 , thereby, further reduce the potential of noise (e.g., jitter) in the waveform signals SIG A  and SIG B . Outputs of the threshold detectors  401  and  402  are provided as inputs to respective J out of K majority vote modules  416  and  418 . 
   The waveform signals SIG A  and SIG B  are comprised of quantized samples, as discussed with regard to  FIG. 1A  above. Therefore, some of the signal samples will exceed the threshold value of their respective detection circuits  401  and  402 , and some will not. Of the signal samples that exceed the detection threshold value and are provided as inputs to the respective majority vote modules  416  and  418 , some may still be purely noise. 
   The majority vote modules  416  and  418  are therefore provided to further filter and smooth pulses in the waveforms SIG A  and SIG B . The pulse (P) represents, shown in  FIG. 2 , is an exemplary depiction of one of these pulses. The smoothing provided by the voting modules  416  and  418  ultimately further enhance the reliability of eventual pulse width measurements. Majority voting modules are well understood by those of skill in the art. 
   For purpose of review, however, majority voting entails the use of a sliding window having a predetermined width (e.g., K number of samples). In the present invention, this sliding window is used to compare K samples from one signal (e.g., SIG A ) with corresponding samples from another signal (e.g., SIG B ). The sliding window begins, for example, with each of the first K samples from the signal SIG A  compared with a corresponding (twin) sample from the signal SIG B . Since the window slides through the entire signal one pulse at a time (or some other programmable value), each sample within the window is compared with its twin K times. Out of these K comparisons between twins (corresponding pulse), the twins must match (match based upon user determined classifiers) J out of the K comparisons. 
   In the majority vote modules  416  and  418  of  FIG. 4 , for example, the respective output samples will form relatively clean (e.g., square wave) pulses that have maintained fairly sharp rising and falling edges, despite the presence of noise. The clean (square wave) pulses can then be used for detection and measurement of their pulse widths (i.e., TOA/TOE difference). Outputs of the majority vote modules  416  and  418  are provided as inputs to a TOA/TOE detection module  420 . The TOA/TOE detection module  420  senses and then records the TOA and TOE of the pulses associated with the signals SIG A  and SIG B . 
   Referring back to  FIG. 2  and discussed above, the rising and falling edges of the signal SIG A  occur quickly and are therefore good determinants for accurately measuring the TOA and the TOE. However, since the waveform signal SIG A  is faster, it is also more susceptible to noise. Thus, although the samples of the waveform signal SIG A  are more accurate with respect to time, there is a lower confidence that these samples represent a valid pulse. That is, these samples could still be noise. 
   On the other hand, the rising and falling edges of the waveform signal SIG B  occur gradually and more slowly than those of the signal SIG A . Correspondingly, the waveform signal SIG B  is less susceptible to noise than the waveform signal SIG A . Thus, when waveform samples associated with the signal SIG B  exceed the threshold of the detector  401 , there greater confidence that an actual signal pulse is present. 
   For these reasons, the TOA/TOE detector  420  relies on the waveform signal SIG A  for actual TOA/TOE detection  422  (i.e., recording of the TOA/TOE numerical values) since it is faster. Once the TOA/TOE numerical values (derived from the signal SIG A ) are recorded, the detector  420  then uses the TOA/TOE of the signal SIG B  for purpose of confirmation  424 . That is, the detector  420  relies on the TOA/TOE values of the signal SIG B  to confirm that the recorded TOA/TOE values for the signal SIG A  represent an actual pulse and not noise. 
   The receiving system  100  can be configured to provide TOA/TOE measurements in a number of different ways, based upon user requirements/preferences. For example, the TOA/TOE value  422 , output from the detector  420 , can be used as an independent measurement of the width (W P ) of the exemplary pulse (P). Similarly, the TOA/TOE value  306 , output from the peak/dip detector  304 , can also be used as an independent measurement of the width (W P ) of the pulse (P). In yet another more complimentary configuration, the TOA/TOE detection values  422  and  306  can be averaged together, or compared, to produce an even more robust and reliable measurement of the width (W P ) of the pulse (P). 
     FIG. 5  is an exemplary method  500  of practicing an embodiment of the present invention. In  FIG. 5 , a received pulse width coded signal is digitized, as indicated in step  502 . In step  504 , the digitized signal is transformed to at least one of power domain and absolute value domain to produce a converted signal. In steps  506  and  508 , a signal power of the converted signal is estimated using (i) a wide band filter to produce data representative of a first signal having first type signal shape properties and (ii) a narrow band filter to produce data representative of a second signal having second type signal shape properties. The first and second signal data are then compared to produce information representative of pulse width characteristics of the received signal, as shown in step  510 . 
   CONCLUSION 
   The present invention provides a new receiver architecture that uses power detection for robust and accurate pulse width measurements in the presence of noise. A pre-processing system provides an initial level of analysis of signal spectral data to be used for measurements. The analyzed data is then provided to two independent processing systems, each using a unique technique to measure, for example, a signal&#39;s pulse width. Based upon user preferences, the two systems can be used separately or in complimentary fashion to provide significantly more reliable measurements of pulse width. 
   The present invention has been described above with the aid of functional building blocks illustrating the performance of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. 
   Any such alternate boundaries are thus within the scope and spirit of the claimed invention. One skilled in the art will recognize that these functional building blocks can be implemented by analog and/or digital circuits, discrete components, application-specific integrated circuits, firmware, processor executing appropriate software, and the like, or any combination thereof. Thus, the breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents. 
   The foregoing description of the specific embodiments will so fully reveal the general nature of the invention that others can, by applying knowledge within the skill of the art (including the contents of the references cited herein), readily modify and/or adapt for various applications such specific embodiments, without undue experimentation, without departing from the general concept of the present invention. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance presented herein, in combination with the knowledge of one of ordinary skill in the art.