Abstract:
An underwater communications method and apparatus is provided for demodulating communications signals while compensating for the effects of range rate, i.e., relative velocity between the nodes of the communication system. The method of the invention is implemented in the DSP of an underwater bi-directional acoustic modem and method comprises the steps of generating a communication signal with an acquisition component for providing an initial estimate of the range rate. The acquisition component preferably is with a nonlinear frequency modulated acquisition component, preferably in the form of a hyperbolic frequency modulated signal, for providing the initial estimate of the range rate. Following this, a second set of signals, preferably a set of single frequency tonals, is generated and acquired using the initial estimate of range rate to obtain a more precise estimate of range rate. The communication signal is then demodulated using the more precise estimate of range rate to compensate for the effects of range rate on the communication signal so that the communication signal appears to have not been influenced by the effects of range rate.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
   This application claims the benefit of priority from U.S. Provisional Patent Application No. 60/525,558 filed on Nov. 26, 2003 with the title HIGH RANGE RATE SIGNALING, the entire contents of which are incorporated herein by reference. 

   FIELD OF THE INVENTION 
   This invention in general relates to underwater communications and in particular to a signal component for use in underwater communications via acoustic modem to provide acquisition and alignment of signals between transmission and receiving nodes that are rapidly moving (20 or more knots) with respect to one another. 
   BACKGROUND AND INVENTION 
   Modems were developed to allow computers to exchange information over a network of telephone lines. To process information, a computer reduces data to a digital format of 1&#39;s and 0&#39;s, representing the two values by either the presence or absence of an electronic signal. The modem, which is short for modulation/demodulation, converts this digital representation to sounds which, in turn, are coded by the telephone lines as electrical signals. In this modulated or analog format, the digital 1&#39;s and 0&#39;s are represented by different frequencies within a defined bandwidth. At the receiving end of the transmission, another modem converts the signal from frequency form back to digital form so that the data can be accepted and processed by the receiving computer. 
   The key performance parameter for a modem is its data transfer rate, which is usually measured by baud rate, or the number of bits per second the modem can reliably generate and receive. Baud rates of 28,800 and 56,600 are now commonplace in PC communications. 
   On land, the medium between modems is the benign environment of a shielded wire or the sharply defined path of a microwave transmission. In these environments, it is relatively easy to achieve fast and reliable transmission of large amounts of data. Without much interference, the discrete signals can be sent out in very close proximity and still be properly understood at the receiving end. And, as signals begin to fade over distance, network facilities recondition the signals so that they arrive in a clear, unambiguous form. 
   Unfortunately, in many underwater applications, a wire connection with submerged instrumentation is either prohibitively expensive or not feasible. The solution is to use the water itself as the medium for the transmission of acoustic signals. However, this solution presents several problems. First, sound travels through water at a much slower speed—approximately 1,500 meters per second—compared to electrical transmissions on a phone line, which travel at the speed of light. 
   Secondly, the water is an open channel into which the acoustic signal is broadcast. Even when the transmission is a narrow beam aimed at its target, the sound wave fans out and generates echoes which arrive at the target destination shortly after the original signal. These multipath echoes require additional processing as the signal is received. 
   The open-channel broadcast also results in the need for additional signal processing with each transmission to assure that the target, and only the target, receives the message. Finally, water can be a much more hostile environment. The signal is affected by changes in water temperature, turbulence, objects in the water and a host of other factors, including any relative motion between communication nodes. 
   With any wireless communications system provisions must be made to accommodate rapid relative velocity between transmitters and receivers of the system. This is especially true of underwater communications, which have relatively limited bandwidths and otherwise difficult channels. All communications signals contain components used for acquisition and alignment, where, in the broadest sense, alignment pertains to both the temporal and spectral identification of the modulated portion of the larger signal. A typical signal component is a linear frequency modulated (LFM) waveform (also known as a chirp). This is processed with a “matched filter” technique using as a filter an exact replica of the transmitted LFM. The peak of the filtered output indicates the arrival time of the signal. When relative velocity (i.e., range rate) occurs, the waveform is distorted by temporal compression or dilation, which also has the effect of compressing/dilating the spectral content of the waveform. In this case, the basic filter is no longer a good “match” for the received signal. The distortion causes a decrease in the peak filtered response, as well as loss of precision in estimation of temporal alignment. Furthermore, the level of spectral distortion of the signal is not revealed. The issue here is to develop an acquisition/synchronization subsystem which can provide acquisition of a packet and provide satisfactory alignment with the modulated message over a wide span of range rates. At the same time the acquisition must provide initial estimation of the range rate so the remainder of the signal can be corrected to enable the demodulation to proceed as if there were no motion present. 
   The classic method for solving this problem is to form a multi-hypothesis, maximum likelihood estimator, wherein a “bank” of filters are formed, each reflecting a different hypothesis of range rate. The number of filters used must account for the degree of spectral distortion imposed by the motion. Typically, a new filter must be used when the adjacent filter peak is reduced by 50%. The system then observes all of the filtered outputs and chooses that one with the largest peak. This “best” choice of filter then determines the range rate, which can then be used to correct the remainder of the signal for the imposed spectral distortion. 
   The approach just described is considered optimal under typical conditions of an additive white Gaussian noise channel. However, the computational burden is very high, and, may be prohibitive for a small, battery-powered digital signal processor (DSP). 
   A principal purpose of this invention is to provide an alternative transmission/acquisition signal, which is robust in the presence of range rate, and which is combined with a secondary signal to identify the range rate where the combination of the two is used for purposes of both temporal and spectral alignment. 
   Another purpose of this invention is to provide improved underwater acoustic modems that can conduct bi-directional communication while moving at high speeds relative to one another. 
   Other objects of the invention will, in part, be obvious and will, in part, appear hereinafter when the following detailed description is read in conjunction with the drawings. 
   SUMMARY OF THE INVENTION 
   An underwater communications method is provided for demodulating communications signals while compensating for the effects of range rate, i.e., relative velocity between the nodes of the communication system. In one aspect, the method comprises the steps of generating a communication signal with an acquisition component for providing an initial estimate of the range rate. The acquisition component preferably is with a nonlinear frequency modulated acquisition component for providing the initial estimate of the range rate wherein the frequency of the nonlinear frequency modulated acquisition component varies in accordance with the expression 
               (     1   +     v   c       )     ⁢   f     ,         
where ν is the constant velocity between the transmitter and receiver, c is the velocity of propagation of sound in water, f is the frequency of modulation which varies from a first frequency to a last frequency, f 1 ≦f≦f n . More particularly, the nonlinear frequency modulated acquisition component is a hyperbolic frequency modulated signal.
 
   Following this, a second set of signals is generated and acquired using the initial estimate of range rate to obtain a more precise estimate of range rate. The second set of signals is preferably a set of single frequency tonals. 
   The communication signal is then demodulated using the more precise estimate of range rate to compensate for the effects of range rate on the communication signal so that the communication signal appears to have not been influenced by the effects of range rate. 
   The method is implemented via software programmed on a conventional data signal processor (DSP) forming part of a well-known underwater bi-directional acoustic modem. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The structure, operation, and methodology of the invention, together with other objects and advantages thereof, may best be understood by reading the detailed description in connection with the drawings in which each part has an assigned numeral that identifies it wherever it appears in the various drawings and wherein: 
       FIG. 1  is a diagrammatic perspective view of an underwater communications environment in which the communications nodes are moving relative to one another; 
       FIG. 2  is a block diagram of a modem in accordance with the invention; 
       FIG. 3  is a high level flowchart of the method of the invention; 
       FIG. 4  is a block diagram of a transmitter and receiver of the invention; and 
       FIG. 5  is a graph of the output of the correlation for one reference signal and nine examples of range rate spanning −20 to +20 kts.; and 
       FIG. 6  is a graph showing by the “x” the number of temporal samples by which a peak is offset from the zero-range-rate peak. 
   

   DETAILED DESCRIPTION 
   The present invention relates to a signal component for use in underwater communications via acoustic modem to provide acquisition and alignment of signals between transmission and receiving nodes that are rapidly moving (20 or more knots) with respect to one another. An example of such an underwater communications system is diagrammatically illustrated in  FIG. 1  in which are illustrated a submarine  12  equipped with an underwater sonar modem including a transducer  14  for transmitting and receiving signals between various communications nodes in the system. 
   Included among the communications nodes are two subsea acoustic modems,  18  and  20 , each of which is equipped with transducers  16  and  22 , respectively, to serve as underwater component of a bi-directional acoustic communication network. The subsea modems may be interfaced with a host instrument, and acoustically transmit/receive data from the host to a topside acoustic modem  24 . 
   At the surface is the topside telesonar modem  24  serves as the surface component of the bi-directional acoustic communication system. The surface modem  24  is configured with a remote dunking transducer  28  and an air resident vertically mounted transducer  26  for communications with surface vessels, aircraft, land or space based nodes and operates to transmit commands/data to, and receive commands/data from, the subsea acoustic modem(s)  18  and  20  located on a seafloor instrumentation package, the submarine  12  or AUV (not shown). 
   The underwater modems are of a well-known type marketed by, for example, Benthos Corporation, North Falmouth, Mass. and are generally configured for bi-directional acoustic communication at data rates up to 2400 baud and provide ultra reliable data transmission in either a vertical or horizontal channel using MFSK modulation schemes, as well as data redundancy, convolutional coding, and multipath guard period ensure robust data transmission. The transducers may be remote or integral in configuration, and may be directional, omnidirectional, or be line array transducers for particular radiation patterns. Standard frequency bands: 9–14 kHz (LF), 16–21 kHz (MF), or 25–30 kHz (HF) may be employed depending on application requirements. All of the components may be under the control of surface based PC equipped with a graphic user interface (GUI) for ease of operation.  FIG. 2  illustrates the general configuration of the modems where one is designated generally at  30 . Modem  30  is seen to comprise an electrical circuit board configured in a well-known manner with a digital signal processor (DSP) for performing computational functions on incoming and outgoing communications signals in accordance with preprogrammed protocols, and to provide other system operational control. A user interface  34  is provided for feeding data, such as configuration instructions, to the DSP. Outgoing signals are modulated and amplified by an amplifier  36  after which they are passed to a transceiver  38 . Transceiver  38  passes incoming signals to a signal conditioner  40  before they are passed to the DSP for demodulation. 
   The DSP is programmed with a high range rate correction program to permit underwater acoustic communications when the nodes of the communications systems are moving at high speeds with respect to one another. 
   For initial signal acquisition, use of a hyperbolic frequency modulated (HFM) signal is made. Such signals have long been employed as sonar signals in anti-submarine warfare (ASW) situations. In this application, their ability to provide adequate detection performance in the presence of substantial range rate (relative speed) with the target submarine is well known. However, the peak arising from the matched filter process on the HFM experiences an unknown temporal offset which is a function of the range rate. This may or may not be of importance in ASW, but the misalignment is a serious problem in the communications context. Therefore, the HFM waveform is followed with a number of single-frequency tonals, all transmitted simultaneously. The number of tonals may be greater than or equal to one. Tonal signals are uniquely suited to producing a Doppler-shift, or spectral shift, which is a function of the range rate and the tonal frequency. Given the approximant alignment provided by the filtering of the HFM, we obtain a substantial portion of the tonals, and compute a power spectrum. The power spectrum is optimally based on a Fourier transform, although other transforms may be used. The tonals will produce peaks in the power spectrum. If these peaks are large enough, their spectral location is estimated and compared with the known transmitted frequency. The difference is the Doppler shift of the tones, from which we can calculate the relative velocity or range rate. The range rates estimated from each of the tonals is averaged to obtain one estimate. This procedure is generally outlined in the flowchart of  FIG. 3 . 
   The range rate estimation from the tonals is used for two purposes. First, via an algorithm described here, the alignment error imposed by range rate on the filtered HFM is corrected. Second, the compression/dilation of the modulated waveform is identified and is compensated for by conventional resampling methods which return the modulated signal to the form it would have had in the absence of range rate. 
   Two HFM waveforms are defined: the stored reference (used as a filter), and the transmitted signal. The latter is a subset of the former both in duration and frequency content. The duration of the reference waveform is T ref , and the duration of the transmitted waveform is T tx . The reference waveform sweeps from F min  to F max , in a manner to be described, while the transmitted waveform sweeps form f min  to f max . 
   The parameters for the transmitted waveform are derived from the anticipated maximum range rate R max  as described below. 
   The replica hyperbolic FM is defined by an inverse relationship:
 
 f= 1/(slope* t+b )  (1)
 
with a solution
 
 x ( t )=exp( i 2π( ln (slope* t+b )/slope− Fc*t ))  (2)
 
where b=1/Fmin, and where the slope is defined to be
 
slope=( F   min   −F   max )/( T   ref   *F   max   *F   min ),  (3)
 
with Fc=( F   max   +F   min )/2;
 
   In Eq. 2, the subtracted factor Fc*t acts as a basebanding function, moving the HFM down from passband at the same time it is generated. With this factor, x(t) may be generated directly at the baseband sample rate of fs samples/second. The signal is constrained so that the bands never exceed the allowable bandwidth of W Hz. Given the maximum range rate of R max , we first compute the band edges for the transmit signal are first computed:
 
factor=1−1.68* R   max /sonic;  (4)
 
dum F=F   min *factor;
 
 f   min =2* F   min −dum F ; % Max low edge of  Tx  signal
 
factor=1+1.68* R   max /sonic;
 
dum F=F   max *factor;
 
 f   max =2* F   max −dum F ; % Max upper edge of  Tx  Signal
 
and the times t 1  and t 2  in the sweep of the signal which correspond to f min  and f max , respectively are computed as:
 
 ts 1=(1 /f   min −1/ F   min )/slope;  (5)
 
 ts 2=(1 /f   max −1 /F   max )/slope;
 
   Because the transmitted signal is shorter than the replica, it needs to be positioned in the outgoing signal with a slight offset, so that the correlator (when no range rate is present), peaks at the correct time. 
   When the transmitted signal is correlated with the received signal, any compression/dilation of the waveform is reflected in a small loss in output SNR due to the extended parameters of the reference. It will also result in the correlator peak being offset from the nominal zero lag position. The offset may be defined theoretically by the relationship:
 
offset=−(( f   min −1)./( F   min *(1 +cf )))/(slope* f   min )−(( f   min −1)./( F   min *(1 +cf )))/(slope* f   min )  (6)
 
where the compression factor is the ratio of range rate (v) to sound speed (sonic):
 
 cf=v /sonic   (7)
 
   When a peak is detected, it is not known that the received signal was perturbed by range rate. Therefore, the HFM is followed with a T tona I ms N-tone signal. This signal consists of N tonals, located at known locations within the transmitted signal band. The power spectrum of this signal is observed and the location of the peaks pertinent to each tone is estimated. The difference between the estimated location and the transmitted location provides data which is used to estimate range rate. Because the FFT used to evaluate the power spectrum may be coarse, it will be necessary to develop an appropriate estimator: let y1, y2, y3 be the power spectral energy in bins located at x1, x2, x3, centered on x2 (y2 is greatest). A quadratic curve is fit to these points, with results:
 
 A= ( y (1)−2* y (2)+ y (3))/2;  (8)
 
 C=y (2);
 
 B=y (3)− y (2)− A; 
 
 X=−B /(2* A );
 
 Y=A*X^ 2 +B*X+C; 
 
 X =( x 1(2)+ X );
 
with X being the desired estimate of bin location, and y2 being the spectral power at X. If B is the FFT bin width in Hertz, the difference between (X−1)*B and the transmitted frequency F k  is Δf k , k=0 . . . N.
 
   With the frequency offset estimate Δf k  available, the range rate is estimated as
 
 RR   k =sonic*Δ f   k /(1.68* F   k )  (9)
 
   We compute the average RR over RR k  to obtain our estimate of range rate. Given the range rate, the compression factor is calculated as follows:
 
 cf=RR* 1.68/sonic; ( RR  in knots)
 
   Alternatively, we can normalize the frequency shift to fc as follows:
 
Δ f   c   =Δf   k   *f   c /( f   c+ ( f   c−   f   k ))
 
   We then calculate the mean of Δf c . Given the average Δf cavg , the compression factor is calculated as follows:
 
 cf=Δf   cavg   /f   c 
 
   Given the compression factor, the correction to the temporal offset inherent in the matched filter output is estimated as
 
offset=− fs* (( f   min −1)./( F   min *(1 +cf )))/(slope* f   min )−(( f   min −1)./( F   min *(1 +cf )))/(slope* f   min )
 
   The result “offset” is presented in temporal samples. 
   This foregoing procedure is implemented by way of the transmitter and receiver shown, respectively, as  50  and  60  in  FIG. 4 . As shown in block  52 , a hyperbolic frequency modulated waveform (HFM) is first transmitted. Following this, one or more single frequencies tonals are transmitted as shown in block  54 . Afterwards, a message modulated communications waveform is transmitted as shown in block  56 . 
   At receiver  60 , the signals from the transmitter  50  are first received and the HFM is match filtered as shown in block  62 . Following this, an initial alignment estimate is made as in block  64 . Then the tonal waveform is captured in block  66 . The power spectrum of the tonal waveform is then computed in block  68 . From the power spectrum of the tonals, the received frequencies are then estimated in block  70 . Then in block  72 , the differences between the original and measured frequencies are measured. In block  74 , an estimate of the range rate is made and the initial arrival time estimate is refined. In block  76 , the modulated communications waveform are captured, and estimates to correct alignment and to remove compression/dialation factors are applied. 
     FIG. 5  shows, the output of the correlation for one reference signal and nine examples (curves  80  through  96 ) of range rate spanning −20 to +20 kts. (higher relative speeds, such as +/−30 knots or higher are possible). All signals “arrived” at the same time, but the correlation process introduced the apparent offsets.  FIG. 6  shows by the “x” the number of temporal samples by which a peak is offset from the zero-range-rate peak. The “o” is the theoretical measurement (Eq (6)), when multiplied by fs, while the “+” shows the offset estimated from the CW tones. This agreement shows the alignment offset caused by using the extended reference HFM can be corrected, given the tri-tones to estimate frequency offset. Note that the frequency offset may also be used to set the resampling of the modulated packet, thereby removing the effects of range rate. 
   It should be noted that the tri-tones may not behave as well as shown here. Should there be frequency-dependent fading, it will be necessary to ignore a faded tone. This can only be done if the local noise floor is known. That is, one should estimate the residual mean (M) and sigma (S) of the power spectrum, and set a threshold at a level of approximately Thresh=M+20*S. Lines greater than Thresh may be included in the calculation. 
   An example of Matlab Code for implementing the high range rate correction protocol is as follows: 
   
     
       
             
           
         
             
                 
             
           
           
             
               %HFM_test a routine to test the ability of an HFM to overcome 
             
             
               range rate, 
             
             
               %and to predict the temporal offset in matched filter output induced by 
             
             
               %range rate. This routine generates one replica for storage, then 
             
             
               %truncates the same signal for transmission. It does not support the 
             
             
               discussion above 
             
             
               %concerning use of CW tones to correct HFM offset. 
             
             
               clear 
             
             
               clf 
             
             
               fs=10240 
             
             
               sonic=5000; %Use your standard sonic speed 
             
             
               %replica 
             
             
               Tref=0.05; %Basic modem acquisition signal duration 
             
             
               fmin=16000; %lower band edge 
             
             
               fmax=21120; %upper band edge 
             
             
               Fc=(fmax+fmin)/2; %carrier 
             
             
               rrmax=20; %maximum velocity in kts 
             
             
               %build the replica HFM at baseband 
             
             
               slope=(fmin−fmax)/(Tref*fmax*fmin); 
             
             
               dt=1/fs; 
             
             
               tr=0:dt:Tref−dt; 
             
             
               ref=exp(i*2*pi*((log(slope*tr+1/fmin)/slope)−Fc*tr)); 
             
             
               %compute Tx signal at baseband 
             
             
               factor=1−1.68*rrmax/sonic; 
             
             
               dumF=fmin*factor; 
             
             
               f1=2*fmin−dumF; %Max low edge of Tx signal 
             
             
               factor=1+1.68*rrmax/sonic; 
             
             
               dumF=fmax*factor; 
             
             
               f2=2*fmax−dumF; %Max upper edge of Tx Signal 
             
             
               %find start and stop times of Tx signal corresponding to f1 &amp; f2 
             
             
               dt=1/fs; 
             
             
               ts1=(1/f1 −1/fmin)/slope; 
             
             
               ts2=(1/f2 −1/fmin)/slope; 
             
             
               Tstart=round(ts1/dt)−1; 
             
             
               Tstop=round(ts2/dt)−1; 
             
             
               signal=ref(Tstart:Tstop); %Tx signal 
             
             
               extra=round((Tref−Tstop*dt)*fs); 
             
             
               %following signal is exactly as long as is the reference signal, so 
             
             
               %correlation peaks at the same point in time 
             
             
               signal=[zeros(1,Tstart−1),signal,zeros(1,extra)]; 
             
             
               ts=0:dt:(length(signal)−1)*dt: 
             
             
               %analysis 
             
             
               figure(1) 
             
             
               clf 
             
             
               nfft=2{circumflex over ( )}ceil(log(length(ref))/log(2)); 
             
             
               ff=fs/nfft; 
             
             
               f=0:ff:(nfft−1)*ff; 
             
             
               Rrb=abs(fft(ref,nfft)).{circumflex over ( )}2; 
             
             
               Rsb=abs(fft(signal,nfft)).{circumflex over ( )}2; 
             
             
               subplot(2,1,1),plot(f,Rrb) 
             
             
               hold on 
             
             
               plot(f,Rsb,‘g’); 
             
             
               hold off 
             
             
               z1=abs(cconvolv(ref,[zeros(1,100),ref],1)).{circumflex over ( )}2; 
             
             
               z2=abs(cconvolv(ref,[zeros(1,100),signal],1)).{circumflex over ( )}2; 
             
             
               subplot(2,1,2),plot(z1) 
             
             
               hold on 
             
             
               plot(z2,‘g’) 
             
             
               hold off 
             
             
               %add range rate 
             
             
               delr=rrmax/5; 
             
             
               rr=−rrmax:delr:rrmax; 
             
             
               lrr=length(rr); 
             
             
               z=zeros(2*length(signal),lrr); 
             
             
               for k=1:lrr, 
             
             
                factor=(1+rr(k)*1.68/sonic); 
             
             
                x=dilation(factor,fs,signal,Fc); 
             
             
                zz=abs(cconvolv(ref,[zeros(500,1);x(:)],1)).{circumflex over ( )}2; 
             
             
                z(1:length(zz),k)=zz(:); 
             
             
               end 
             
             
               center=fix(lrr/2)+1; 
             
             
               [dum,iz1]=max(z(:,center)); 
             
             
               figure(2) 
             
             
               clf 
             
             
               subplot(2,1,1),plot(z(450:550,:)) 
             
             
               offset=zeros(lrr,1); 
             
             
               measured=offset; 
             
             
               min_measure=− ((f1−1)./((fmin)))/(slope*f1); 
             
             
               for k=1:lrr, 
             
             
                factor=(1+rr(k)*1.68/sonic); 
             
             
                offset(k)=fix((− ((f1−1)./((fmin)*(factor)))/(slope*f1)−min —   
             
             
                measure)*fs); 
             
             
                [dum iz]=max(z(:,k)); 
             
             
                measured(k)=iz1−iz; 
             
             
               end 
             
             
               subplot(2,1,2),plot(offset,‘o’) 
             
             
               hold on 
             
             
               plot(measured,‘+g’) 
             
             
               hold off 
             
             
                 
             
           
        
       
     
   
   Having described the invention with reference to particular embodiments, other variations will occur to those skilled in the art based on its teachings, and it is intended that all such variants be within the scope of the invention as defined by the appended claims.