Abstract:
The invention relates to supporting an acquisition of a signal, wherein the signal comprises a sequence of complex valued samples, wherein the acquisition comprises an integration of the complex valued samples in subsequent integration intervals, and wherein the signal may be subject to a frequency drift. In order to enable an improved acquisition, a phase angle is estimated in the signal in a respective integration interval (step  504 ). The samples are adjusted based on the estimated phase angle in a respective integration interval (step  505 ). Only the adjusted samples from a plurality of integration intervals are then integrated (step  507, 508 ).

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is the U.S. National Stage of International Application Number PCT/IB05/000517 filed on Mar. 1, 2005 which was published in English on Sep. 8, 2006 under International Publication Number WO 2006/092641. 
       FIELD OF THE INVENTION 
       [0002]    The invention relates to a method for supporting an acquisition of a signal. The invention relates equally to an integration component for supporting an acquisition of a signal, to a signal acquisition module comprising such an integration component, to an electronic device comprising such an integration component, to a communication system comprising such an electronic device, to a software code for supporting an acquisition of a signal and to a software program product storing such a software code. 
       BACKGROUND OF THE INVENTION 
       [0003]    A signal has to be acquired for example in CDMA (Code Division Multiple Access) spread spectrum communications. 
         [0004]    For a spread spectrum communication in its basic form, a data sequence is used by a transmitting unit to modulate a sinusoidal carrier, and then the bandwidth of the resulting signal is spread to a much larger value. For spreading the bandwidth, the single-frequency carrier can be multiplied for example by a high-rate binary pseudo-random noise (PRN) code sequence comprising values of −1 and 1, which code sequence is known to a receiver. Thus, the signal that is transmitted includes a data component, a PRN component, and a sinusoidal carrier component. The term chip is used to designate the bits of the PRN code conveyed by the transmitted signal, as opposed to the bits of the data sequence. 
         [0005]    A well known system which is based on the evaluation of such code modulated signals is GPS (Global Positioning System). In GPS, code modulated signals are transmitted by several satellites that orbit the earth and received by GPS receivers of which the current position is to be determined. Currently, each of the satellites transmits two microwave carrier signals. One of these carrier signals L 1  is employed for carrying a navigation message and code signals of a standard positioning service (SPS). The L1 carrier signal is modulated by each satellite with a different C/A (Coarse Acquisition) code known at the receivers. Thus, different channels are obtained for the transmission by the different satellites. The carrier signal has a frequency of 1575.42 MHz and the C/A code, which is spreading the spectrum over a nominal bandwidth of 20.46 MHz, is repeated every 1023 chips, the epoch of the code being 1 ms. The carrier frequency of the L1 signal is further modulated with the navigation information at a bit rate of 50 bit/s. The navigation information, which constitutes a data sequence, can be evaluated for example for determining the position of the respective receiver. 
         [0006]    A receiver receiving a code modulated signal has to have access to a synchronized replica of the employed modulation code, in order to be able to de-spread the data sequence of the signal. More specifically, a synchronization has to be performed between the received code modulated signal and an available replica code sequence. Usually, an initial synchronization called acquisition is followed by a fine synchronization called tracking. In both synchronization scenarios correlation means are used to find and maintain the best match between the replica code sequence and the received signal and thus to determine the received code phase. The match can be determined for example with chip accuracy. If an accuracy of a fraction of a chip is needed, the chip can be presented by several samples after an analog-to-digital conversion. 
         [0007]    During the acquisition, the phase of the received code modulated signal relative to the available replica code sequence can have any possible value due to uncertainties in the position of the receiver, to uncertainties in the available time and/or to a lack of ephemeris information. 
         [0008]    Moreover, an additional frequency modulation of the received signal may occur, which can be as large as +/−6 kHz due to a Doppler effect and several kHz due to receiver oscillator frequency uncertainty. The search of the received code phase is therefore usually performed with different assumptions on an additional frequency modulation. 
         [0009]    For illustration,  FIG. 1  presents a schematic block diagram of a signal acquisition module  10  of a conventional receiver. 
         [0010]    The code modulated signal is received via an antenna  19  and forwarded to a radio frequency (RF) part  11 . The RF part  11  converts the received signal to the base band using a local oscillator. The base band signal is then converted into the digital domain by an analog-to-digital (AD) converter  12  and enters the digital base band part of the receiver. The resulting samples are mixed by a mixer  13  with a search center frequency ej jωt . 
         [0011]    The signal output by the AD converter  12  has two unknown frequency components, a component resulting from the Doppler effect on the carrier frequency of the received signal and an oscillator error component. The mixer  13  is able to carry out several consecutive searches with different search center frequencies to compensate for such frequency components. 
         [0012]    Optionally, the mixed samples may then be decimated by a decimation block  14  in accordance with a provided code frequency. The mixed and decimated samples are provided to a matched filter  15  to find out the code phase, or delay, of the received signal compared to an available replica code sequence. The matched filter  15  outputs continuously correlation values for each checked code phase. 
         [0013]    The correlation values output by the matched filter  15  are integrated coherently by a coherent integration block  16 . 
         [0014]    For a high sensitivity, which is required in particular in weak signal environments like indoor environments, a receiver normally uses long integrations to achieve a sufficient signal-to-noise ratio for a reliable detection. 
         [0015]    A long-time coherent integration, however, is prevented by the non-coherence of the signal itself, that is, by a changing phase angle of the signal. The phase angle of the signal may change due to various reasons, for instance because the oscillator frequency in the RF part  11  is drifting or because of a drift in the Doppler frequency. It is not possible, for example, to coherently integrate a signal for over one second, if there is a 1 Hz frequency drift of the oscillator. If the drifting frequency is known, it can easily be compensated. If the drifting frequency is not known but linear and thus stable, several frequency bins can be used to ‘test’ it. Unfortunately, though, the frequency drift is not predictable. Mostly, it is not even linear and stable during the required integration time. Such changes cannot be taken into account by assuming various frequency bins, since the signal does not stay in a single frequency bin. The signal energy is rather spread over several frequency bins. 
         [0016]    To deal with this kind of problem, it is known to carry out a partial coherent integration only for a respective period of time during which the coherency of the signal is guaranteed. Subsequently, several coherent results are further combined to enhance the signal. Typically, this further combining is achieved by means of a non-coherent integration, in which only the amplitude of the signal is used. A non-coherent integration has the advantage that the phase of the signal does not have an influence onto the integration result. 
         [0017]    In the example of  FIG. 1 , the coherent integration block  16  is therefore followed by a non-coherent integration block  17 . The non-coherent integration block  17  integrates consecutive coherent integration results by summing the absolute or the squared values of these coherent integration results. New squared values are added for the respective duration of a non-coherent integration period. 
         [0018]    If the assumptions on the code phase and the frequency modulation belonging to one combination are correct for the received code modulated signal, then the correlation results in a larger integration value than in the case of a misalignment or an inappropriate compensation of a frequency modulation. A peak detector  18  is thus used for detecting the correlation peak and for comparing it with a certain threshold, in order to find the correct code phase and the correct frequency of modulation. 
         [0019]    An acquisition making use of short coherent integrations which are followed by a non-coherent integration is described for example in U.S. Pat. No. 6,606,346 B2. 
         [0020]    The price paid for the non-coherent integration, however, is a so-called ‘squaring loss’ resulting from the loss of the phase information. The problem is getting worse for a weak signal acquisition when the signal-to-noise ratio is far below zero decibels. 
         [0021]    It has to be noted that a similar problem may occur with any other receiver of code modulated signals, in particular with any other receiver for a Global Navigation Satellite System (GLASS). 
       SUMMARY OF THE INVENTION 
       [0022]    The invention enables an improved signal acquisition. 
         [0023]    A method for supporting an acquisition of a signal is proposed, wherein the signal comprises a sequence of complex valued samples, wherein the acquisition comprises an integration of these complex valued samples in subsequent integration intervals, and wherein the signal may be subject to a frequency drift. The method comprises estimating at least one phase angle in the signal in a respective integration interval. The method further comprises adjusting the samples based on the at least one estimated phase angle in a respective integration interval. The method further comprises integrating adjusted samples from a plurality of integration intervals. 
         [0024]    Moreover, an integration component for supporting an acquisition of a signal is proposed, wherein the signal comprises a sequence of complex valued samples, wherein the acquisition comprises an integration of the complex valued samples in subsequent integration intervals, and wherein the signal may be subject to a frequency drift. The integration component comprises a phase estimator adapted to estimate at least one phase angle in a signal, which is to be acquired, in a respective integration interval. The integration component further comprises a signal rotator adapted to adjust complex valued samples of a signal, which is to be acquired, based on at least one phase angle estimated by the phase estimator for a respective integration interval. The integration component further comprises an adaptive integrator adapted to integrate adjusted samples of a plurality of integration intervals provided by the signal rotator. 
         [0025]    Moreover, a signal acquisition module is proposed, which comprises such an integration component. 
         [0026]    Moreover, an electronic device is proposed, which comprises such an integration component. 
         [0027]    Moreover, a communication system is proposed, which comprises such an electronic device and a network element of a communication network. 
         [0028]    Moreover, a software code for supporting an acquisition of a signal is proposed, wherein the signal comprises a sequence of complex valued samples, wherein the acquisition comprises an integration of the complex valued samples in subsequent integration intervals, and wherein the signal may be subject to a frequency drift. When running in an electronic device, the software code realizes the steps of the proposed method. 
         [0029]    Finally, a software program product is proposed, in which the proposed software code is stored. 
         [0030]    The invention proceeds from the consideration that frequency drifts in a signal can be compensated at least before a final integration is performed. It is therefore proposed that, in contrast to a conventional coherent integration, a phase angle in a particular integration interval is first estimated and corrected, before a signal part in a first integration interval is combined with signal parts from other time intervals. The indication that frequency drifts are to be compensated at least before a final integration is performed means that it is possible that some integration has already been performed before the compensation. For instance, if a full length matched filter operation is used, then the signal is already coherently integrated over one full code. Further, a coherent integration for a short period, for instance 4 ms, may be performed before the phase angle correction, in order to increase the reliance of the phase estimation. But the integration part that is performed after the phase angle correction will usually be the main part of the integration. 
         [0031]    The signal which is to be acquired according to the invention is a signal which is to be subjected to an integration. This signal can be obtained, for example, by correlating a down-converted, code modulated RF signal with an available replica code sequence in various integration intervals, for example by means of a matched filter. Thus, it is to be understood that the support of acquisition according to the invention implies as well, for example, a support of an acquisition of a received code modulated signal. 
         [0032]    It is an advantage of the invention that it allows an efficient integration of a signal comprising a frequency drift. In enables in particular long integration times in spite of irregular phase changes. The presented approach is very robust, for instance, against frequency drifts of an oscillator which is used for down-converting an RF code modulated signal. The presented approach is equally robust against a Doppler frequency in a received code modulated signal. The presented approach works as well with a very low signal-to-noise ratio (SNR). It may be used by itself or as a complement to a conventional integration employed for a signal acquisition. 
         [0033]    In one embodiment of the invention, the complex valued samples of a respective integration interval of the signal are first divided into groups. A phase angle is then estimated and compensated separately for each group. 
         [0034]    In one embodiment of the invention, the estimation of a phase angle in the signal in a respective integration interval takes account of an assumed shape of the signal. When a typical CDMA signal is correlated by a matched filter with an available replica code sequence, for example, the resulting correlation values can be assumed to have a triangular shape. In this case, a middle sample close to the peak of the triangle may be considered with higher weight than the other samples when determining the phase angle. 
         [0035]    Similarly, the SNR could be taken into account when determining the phase angle. 
         [0036]    If the complex valued samples are divided into groups, each group may comprise as many samples as are required for covering the assumed signal shape in the integration interval, that is, as may samples as can be expected to have a significant amplitude. 
         [0037]    In one embodiment of the invention, the adjusted samples are integrated by summing a respective real part of the adjusted samples to the respective real part of the adjusted samples in other integration intervals. 
         [0038]    In one embodiment of the invention, the signal is first duplicated into a plurality of signals, which are shifted against each other by respectively one sample. At least one phase angle in the signal may then be estimated in a respective integration interval for each of the plurality of signals. Further, the samples may be adjusted based on the at least one estimated phase angle in a respective integration interval for each of the plurality of signals. Further, the adjusted samples of a plurality of integration intervals may be integrated for each of the plurality of signals. Finally, the integration results for the plurality of signals may be combined to a single integration result. 
         [0039]    The invention can be implemented in hardware and/or in software. The most computation power is needed for the phase angle estimation and the signal rotation. In a hardware realization, this task can be carried out quickly by the well known Cordic (COrdinate Rotation DIgital Computer) algorithm. 
         [0040]    The invention can be applied in various fields. It may be employed for instance in any receiver of code modulated signals, for example, though not exclusively, for a satellite positioning or Global Navigation Satellite System (GNSS) receiver, like a GPS receiver, a Galileo receiver or a Glonass receiver. It can be employed as well, for example, in an electronic device, like a mobile terminal, which comprises such a receiver. 
     
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
         [0041]    Other objects and features of the present invention will become apparent from the following detailed description considered in conjunction with the accompanying drawings. 
           [0042]      FIG. 1  is a schematic block diagram of a conventional signal acquisition module; 
           [0043]      FIG. 2  is a schematic block diagram of a satellite based navigation system which can be implemented in accordance with an embodiment of the invention; 
           [0044]      FIG. 3  is a schematic block diagram of a coherent integration block of a signal acquisition module in the system of  FIG. 2 ; 
           [0045]      FIG. 4  illustrates the modeled shape of a signal input to the coherent integration block of  FIG. 3 ; and 
           [0046]      FIG. 5  is a flow chart illustrating an operation in the coherent integration block of  FIG. 3 . 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0047]      FIG. 2  is an exemplary positioning system in which a frequency drift compensation according to the invention can be implemented. The frequency drift compensation can be referred to as a ‘Shape and Phase Adaptive Integration’ or SPAI in short. 
         [0048]    The system comprises a mobile terminal  20  of which the position is to be determined, a plurality of GPS satellites SV 1 -SV 3   29  and a mobile communication network  25 . 
         [0049]    The mobile terminal  20  forms an embodiment of an electronic device according to the invention. It is able to communicate with the mobile communication network  25  and is implemented to this end in a conventional manner. 
         [0050]    The mobile terminal  20  comprises in addition a GPS receiver  21 , which is able to receive and process signals transmitted by GPS satellites  29 . The GPS receiver  21  is constructed to this end in a conventional manner, except for a modification of a signal acquisition module  22 . The mobile terminal  20  may receive assistance data from a network element  26  of the mobile communication network  25  and provide this assistance data to the GPS receiver  21  for assisting a signal acquisition. 
         [0051]    The signal acquisition module  22  corresponds to the signal acquisition module  10  presented with reference to  FIG. 1 , except for a SPAI block replacing the coherent integration block  16  and the non-coherent integration block  17  of the signal acquisition module  10   FIG. 1 . 
         [0052]    Such an SPAI block  30 , forming an embodiment of an integration component according to the invention, is presented in  FIG. 3 . 
         [0053]    The SPAI block  30  comprises a sequence duplicator  31 , a phase estimator  32 , a signal rotator  33  and an adaptive integrator  34 . 
         [0054]    The input of the sequence duplicator  31  corresponds to the input of the SPAI block  30 . The output of the sequence duplicator  31  is connected on the one hand to the phase estimator  32  and on the other hand to the signal rotator  33 . An output of the phase estimator  32  is equally connected to the signal rotator  33 . The output of the signal rotator  33  is connected to the adaptive integrator  34 . The output of the adaptive integrator  34  corresponds to the output of the SPAI block  30 . 
         [0055]    The signal acquisition module  22  of the GPS receiver  21  operates in the same manner as described with reference to the signal acquisition module  10  of  FIG. 1 , except for the processing in the SPAI block  30 . Thus, a received code modulated signal is converted to the baseband by an RF part  11 , converted into the digital domain by an A/D converter  12 , mixed with selected search center frequency by a mixer  13 , decimated by a decimator  14 , correlated by a matched filter  15 , possibly including a first coherent integration or followed by a coherent pre-integration, and integrated by the SPAI block  30 . Finally, the peak in the resulting integrated correlation values is determined by a peak detector  18 . 
         [0056]    In a GPS system, the received signal can be assumed to be a typical CDMA signal. If the decimation of such a signal results in two samples per chip, the signal, or delay profile, output by the matched filter  15  has the shape of a triangle that covers three samples.  FIG. 4  illustrates the amplitude of three consecutive samples x n−1 , x n  and x n+1  forming such a triangle. The acquisition task is trying to find the signal peak or peaks in the delay profile. 
         [0057]    The operation in the SPAI block  30  supporting the acquisition will now be described in the following with reference to  FIG. 5 . 
         [0058]    The searching range in the delay profile output by the matched filter  15  is assumed to be N complex valued samples: 
         [0000]        X =( x   1   , x   2   , x   3   , . . . x   n ) 
         [0059]    This delay profile and two additional samples x N+1  and x N+2  are provided to the SPAI block  30  (step  501 ). Each sample corresponds to a respective correlation value, which is determined by the matched filter  15  for a particular code phase. 
         [0060]    The sequence duplicator  31  forms three sequences Y out of the received delay profile X (step  502 ). To this end, the sequence duplicator  31  takes the original delay profile X as a first sequence Y 1 . Further, the sequence duplicator  31  shifts the original delay profile X by one sample and uses the resulting delay profile as a second sequence Y 2 . Further, the sequence duplicator  31  shifts the original delay profile X by two samples and uses the resulting delay profile as a second sequence Y 3 . The resulting sequences are thus: 
         [0000]    
       
         
           
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         [0061]    The sequences Y 1 , Y 2 , Y 3  are then provided to the phase estimator  32  and to the signal rotator  33 . 
         [0062]    The phase estimator  32  considers respectively three consecutive samples to form a group k (step  503 ): 
         [0000]    
       
         
           
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         [0063]    The presented frequency drift compensation is based on the consideration that the signal peak might be in the middle of any group. 
         [0064]    Since the signal shape covers three samples, only three sequences Y are needed. If the signal shape covers more chips, more sequences are needed with a shift by one sample for each group. The number of the groups in each sequence depends on the length of the delay profile or the acquisition searching range. 
         [0065]    The phase estimator  32  estimates the phase in each group, taking account of the assumed signal shape (step  504 ). The phase estimator  32  assumes for each of the 3-sample groups that the peak might be given by the middle sample x n  of the group. In order to correct the phase of the signal before the integration with other copies of the delay profile, a phase estimation is performed for each group. The phase estimation is based on the principle of the maximum ratio combination for all the samples in the group. In the present example, the phase for group k, with k=1 to N/3, of sequence s, with s=1 to 3, at the present time period T is estimated to be: 
         [0000]        ψ T,k   s   =angle[ x   n +ξ( x   n−1   +x   n+1 )] 
         [0066]    In this equation, x n−1  represents the first sample, x n  the second and thus middle sample, and x n+1  the last sample in the respective group k. Further, ξ is a combination factor that depends on the signal shape and the SNR. The operator angle[ ] takes the phase of the complex sum defined within the brackets. 
         [0067]    In an alternative phase estimation, the phase is estimated for each sample, and the resulting phases are then weighted and added: 
         [0000]    
       
         
           
             
               
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         [0000]    where ζ is another combination factor that depends on the signal shape and the SNR. 
         [0068]    If the phase change is not fast, the phase estimation can be extended over several time periods T. That is, if it is known that the phase is not changing rapidly but stays the same over many input sample groups k, the same estimated phase value can be used without calculating a new one. 
         [0069]    The phase estimator  32  provides the estimated phase  ψ T,k   s    for each group of each sequence Y to the signal rotator  33 . 
         [0070]    The signal rotator  33  tries to approximate the signal phase to zero in each group in the sequences Y received from the sequence duplicator  31  so that an adaptive integration can be done over different time periods T. 
         [0071]    The signal rotator  33  performs to this end a rotation of all samples x m  in each group k by a negative value −  ψ T,k   s    of the phase estimated for this group k (step  505 ): 
         [0000]        x′   m   =x   m ·exp{  ψ T,k   s   } {=m=n−1,  n+ 1} 
         [0072]    After the rotation, the signal rotator  33  arranges the real values of the rotated samples for each sequence in a respective real array (step  506 ): 
         [0000]    
       
         
           
             
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                               3 
                               ′ 
                             
                             , 
                             
                               
                                 x 
                                 4 
                                 ′ 
                               
                                
                               
                                   
                               
                                
                               … 
                             
                              
                             
                                 
                             
                             , 
                             
                               x 
                               
                                 N 
                                 + 
                                 1 
                               
                               ′ 
                             
                           
                           ) 
                         
                       
                     
                   
                 
                 
                   
                     
                       
                         Y 
                         
                           3 
                            
                           ′ 
                         
                       
                       = 
                       
                         real 
                          
                         
                           ( 
                           
                             
                               x 
                               3 
                               ′ 
                             
                             , 
                             
                               x 
                               4 
                               ′ 
                             
                             , 
                             
                               
                                 x 
                                 5 
                                 ′ 
                               
                                
                               
                                   
                               
                                
                               … 
                             
                              
                             
                                 
                             
                             , 
                             
                               x 
                               
                                 N 
                                 + 
                                 2 
                               
                               ′ 
                             
                           
                           ) 
                         
                       
                     
                   
                 
               
             
           
         
       
     
         [0073]    These real arrays Y 1′ , Y 2′ , Y 3′  are then provided by the signal rotator  33  to the adaptive integrator  34 . 
         [0074]    The adaptive integrator  34  aligns the real arrays Y 1′ , Y 2′ , Y 3′  resulting for the current integration time T and adds them to summed up real arrays Y 1′ , Y 2′ , Y 3′ , respectively, of preceding integration times T to obtain a better SNR (step  507 ): 
         [0000]    
       
         
           
             
               Z 
               ′ 
             
             = 
             
               
                 { 
                 
                   
                     
                       
                         
                           Z 
                           
                             1 
                              
                             ′ 
                           
                         
                         = 
                         
                           ( 
                           
                             
                               z 
                               1 
                               
                                 1 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               2 
                               
                                 1 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               3 
                               
                                 1 
                                  
                                 ′ 
                               
                             
                             , 
                             … 
                              
                             
                                 
                             
                             , 
                             
                               z 
                               N 
                               
                                 1 
                                  
                                 ′ 
                               
                             
                           
                           ) 
                         
                       
                     
                   
                   
                     
                       
                         
                           Z 
                           
                             2 
                              
                             ′ 
                           
                         
                         = 
                         
                           ( 
                           
                             
                               z 
                               1 
                               
                                 2 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               2 
                               
                                 2 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               3 
                               
                                 2 
                                  
                                 ′ 
                               
                             
                             , 
                             … 
                              
                             
                                 
                             
                             , 
                             
                               z 
                               N 
                               
                                 2 
                                  
                                 ′ 
                               
                             
                           
                           ) 
                         
                       
                     
                   
                   
                     
                       
                         
                           Z 
                           
                             3 
                              
                             ′ 
                           
                         
                         = 
                         
                           ( 
                           
                             
                               z 
                               1 
                               
                                 3 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               2 
                               
                                 3 
                                  
                                 ′ 
                               
                             
                             , 
                             
                               z 
                               3 
                               
                                 3 
                                  
                                 ′ 
                               
                             
                             , 
                             … 
                              
                             
                                 
                             
                             , 
                             
                               z 
                               N 
                               
                                 3 
                                  
                                 ′ 
                               
                             
                           
                           ) 
                         
                       
                     
                   
                 
                 } 
               
               = 
               
                 ( 
                 
                   
                     
                       
                         
                           ∑ 
                           T 
                         
                          
                         
                             
                         
                          
                         
                           Y 
                           T 
                           
                             1 
                              
                             ′ 
                           
                         
                       
                     
                   
                   
                     
                       
                         
                           ∑ 
                           T 
                         
                          
                         
                             
                         
                          
                         
                           Y 
                           T 
                           
                             2 
                              
                             ′ 
                           
                         
                       
                     
                   
                   
                     
                       
                         
                           ∑ 
                           T 
                         
                          
                         
                             
                         
                          
                         
                           Y 
                           T 
                           
                             3 
                              
                             ′ 
                           
                         
                       
                     
                   
                 
                 ) 
               
             
           
         
       
     
         [0075]    The total number of integration times T can be as large as necessary. Steps  501  to  507  are repeated to this end T times (step  508 ). 
         [0076]    Finally, the adaptive integrator  34  shifts the samples of the resulting sequences Z′ back to the original position. That is, sequence Z 2 ′ is shifted back by one sample, and sequence Z 3 ′ is shifted back by two samples. The final delay profile Z for the acquisition is then obtained by combining corresponding samples in the sequences. Shifting and combining the samples can be represented by the following equation: 
         [0000]    
       
         
           
             
               z 
               j 
             
             = 
             
               
                 ∑ 
                 
                   s 
                   = 
                   0 
                 
                 2 
               
                
               
                   
               
                
               
                 
                   z 
                   
                     s 
                     + 
                     j 
                   
                   
                     s 
                     + 
                     
                       1 
                        
                       ′ 
                     
                   
                 
                  
                 
                   ( 
                   
                     
                       j 
                       = 
                       1 
                     
                     , 
                     2 
                     , 
                     3 
                     , 
                     … 
                      
                     
                         
                     
                     , 
                     N 
                   
                   ) 
                 
               
             
           
         
       
     
         [0077]    The resulting delay profile Z=(z 1 , z 2 , z 3 , . . . , z N ) is the delay profile which is used by the peak detector  18  for the final acquisition. 
         [0078]    Summarized, a new signal acquisition approach is introduced, in which the signal shape and the phase change in a particular time interval are first estimated and then corrected before the signal is combined with signals from other time intervals. The method is very robust against an oscillator frequency drift, especially for long integration times, as can be verified by simulations. 
         [0079]    If there is no frequency drift, the best integration approach is a coherent integration. If the signal coherency cannot be kept during the integration, a non-coherent integration can be performed. Thus, the coherent integration is the ceiling and the non-coherent integration is the floor for an efficient integration in case of a frequency error drift. Simulations show that the presented SPAI results in an acquisition probability between the ceiling and the floor when the Doppler frequency is zero. This means that the proposed SPAI is better than the non-coherent integration but not as good as the coherent integration. If there is a small frequency drift, for example, 6 Hz Doppler against 100 ms integration time, the performance of the coherent integration deteriorates significantly, while the acquisition probability achieved with the other two approaches stays almost the same. In this case, the presented SPAI is much better than the coherent integration. The frequency drift is a big problem especially for a long-time coherent integration. The presented SPAI corrects the signal phase at each time interval and is therefore much more robust to a frequency change than a coherent integration. 
         [0080]    Another kind of simulation may be used for evaluating the performance of the presented SPAI at different SNR levels and different integration times. It shows that SPAI can work at very low SNR and that the SPAI is convergent. This means that in order to achieve a higher acquisition probability under low SNR, the integration times can be increased without having to take care of the frequency drift. 
         [0081]    It is to be noted that the described embodiment constitutes only one of a variety of possible embodiments of the invention. The SPAI block can be implemented by a computer readable medium embodied with software code for execution by a processor so as to implement the above described operation. 
         [0082]    While there have been shown and described and pointed out fundamental novel features of the invention as applied to preferred embodiments thereof, it will be understood that various omissions and substitutions and changes in the form and details of the devices and methods described may be made by those skilled in the art without departing from the spirit of the invention. For example, it is expressly intended that all combinations of those elements and/or method steps which perform substantially the same function in substantially the same way to achieve the same results are within the scope of the invention. Moreover, it should be recognized that structures and/or elements and/or method steps shown and/or described in connection with any disclosed form or embodiment of the invention may be incorporated in any other disclosed or described or suggested form or embodiment as a general matter of design choice. It is the intention, therefore, to be limited only as indicated by the scope of the claims appended hereto. Furthermore, in the claims means-plus-function clauses are intended to cover the structures described herein as performing the recited function and not only structural equivalents, but also equivalent structures. Thus although a nail and a screw may not be structural equivalents in that a nail employs a cylindrical surface to secure wooden parts together, whereas a screw employs a helical surface, in the environment of fastening wooden parts, a nail and a screw may be equivalent structures.