US20010000660A1 - Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms - Google Patents

Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms Download PDF

Info

Publication number
US20010000660A1
US20010000660A1 US09730316 US73031600A US2001000660A1 US 20010000660 A1 US20010000660 A1 US 20010000660A1 US 09730316 US09730316 US 09730316 US 73031600 A US73031600 A US 73031600A US 2001000660 A1 US2001000660 A1 US 2001000660A1
Authority
US
Grant status
Application
Patent type
Prior art keywords
signal
plurality
signals
segments
analog
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
US09730316
Other versions
US6380879B2 (en )
Inventor
Wolfgang Kober
John Thomas
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Data Fusion Corp
Original Assignee
Data Fusion Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Images

Classifications

    • HELECTRICITY
    • H03BASIC ELECTRONIC CIRCUITRY
    • H03MCODING; DECODING; CODE CONVERSION IN GENERAL
    • H03M1/00Analogue/digital conversion; Digital/analogue conversion
    • H03M1/12Analogue/digital converters
    • H03M1/1205Multiplexed conversion systems
    • H03M1/121Interleaved, i.e. using multiple converters or converter parts for one channel
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S1/00Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith
    • G01S1/02Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith using radio waves
    • G01S1/04Details
    • G01S1/045Receivers
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/021Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28Details of pulse systems
    • G01S7/285Receivers

Abstract

The method and apparatus of the present invention is directed to architectures for signal processing, such as for performing analog-to-digital and digital-to-analog conversions, in which the source signal is decomposed into subband signals by an analysis filter, processed, and the processed subband signals combined to form a reconstructed signal that is representative of the source signal.

Description

  • [0001]
    The present application claims priority from U.S. Provisional Application Ser. Nos. 60/087,036 filed May 28, 1998; 60/056,455 filed Aug. 21, 1997; and 60/056,228 filed Aug. 21, 1997, all of which are incorporated herein by this reference.
  • FIELD OF THE INVENTION
  • [0002]
    The present invention relates generally to a method and apparatus for acquiring wide-band random and pseudorandom noise encoded waveforms and specifically to a method and apparatus for acquiring wide-band signals, including deterministic signals, random signals and pseudorandom noise encoded waveforms that divides the waveform into a plurality of subbands prior to signal processing thereof.
  • BACKGROUND
  • [0003]
    Analog-to-digital converters are devices that convert real world analog signals into a digital representation or code which a computer can thereafter analyze and manipulate. Analog signals represent information by means of continuously variable physical quantities while digital signals represent information by means of differing discrete physical property states. Converters divide the full range of the analog signal into a finite number of levels, called quantization levels, and assigns to each level a digital code. The total number of quantization levels used by the converter is an indication of its fidelity and is measured in terms of bits. For example, an 8-bit converter uses 28 or 256 levels, while a 16-bit converter uses 216 or 65536 levels.
  • [0004]
    During the conversion process, the converter determines the quantization level that is closest to the amplitude of the analog signal at that time and outputs the digital code that represents the selected quantization level. The rate at which the output is created indicates the speed of the converter and is measured in terms of samples per second (sps) or frequency in Hertz (Hz). As will be appreciated, a larger number of bits and therefore quantization levels equates into a finer representation of the analog signal.
  • [0005]
    In designing an analog-to-digital converter, there are a number of considerations. In many applications for example it is desirable that the converter has not only a high rate of speed but also a large number of quantization levels or a high degree of fidelity. Such converters are difficult to build and therefore tend to be highly complex and very expensive. The key reason is that conversion errors and the consequential device layout constraints for reducing such errors, both of which can be ignored at slow speeds, can become significant at high speeds. As a result, in existing converters, high fidelity and high speed are commonly mutually exclusive; that is, the higher the converter speed the lower the converter fidelity and vice versa.
  • SUMMARY OF THE INVENTION
  • [0006]
    It is an object of the present invention to provide an analog-to-digital converter that has a high fidelity and a high speed. Related objectives are to provide such an analog-to-digital converter that is relatively simple and inexpensive.
  • [0007]
    The present invention is directed to a method and apparatus for processing signals, particularly wide-band signals, including deterministic signals, random signals, and signals defined by pseudorandom waveforms with a relatively high degree of fidelity and efficiency at a high speed and at a low cost. The invention is particularly useful for processing wideband signal, including signals defined by broadband signals (i.e., signals having a bandwidth of preferably more than about 1 kHz and more preferably more than about 1 GHz).
  • [0008]
    The signal can be in any suitable form such as electromagnetic radiation, acoustic, electrical and optical.
  • [0009]
    In one embodiment, the method includes the following steps:
  • [0010]
    (a) decomposing the analog or digital signal into a plurality of signal segments (i.e., subband signals), each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
  • [0011]
    (b) processing each of the signal segments to form a plurality of processed signal segments; and
  • [0012]
    (c) combining the processed signal segments into a composite signal that is digital when the signal is analog and analog when the signal is digital. As will be appreciated, the sum of the plurality of signal bandwidths is approximately equivalent to the signal bandwidth. The means for processing the signal segments can include any number of operations, including filtering, analog-to-digital or digital-to-analog conversion, signal modulation and/or demodulation, object tracking, RAKE processing, beamforming, null steering, correlation, interference-suppression and matched subspace filtering.
  • [0013]
    In a particularly preferred application, the signal processing step (b) includes either analog-to-digital or digital-to-analog conversions. The use of signal segments rather than the entire signal for such conversions permits the use of a lower sampling rate to retain substantially all of the information present in the source signal. According to the Bandpass Sampling Theorem, the sampling frequency of the source signal should be at least twice the bandwidth of the source signal to maintain a high fidelity. The ability to use a lower sampling frequency for each of the signal segments while maintaining a high fidelity permits the use of a converter for each signal segment that is operating at a relatively slow rate. Accordingly, a plurality of relatively inexpensive and simple converters operating at relatively slow rates can be utilized to achieve the same rate of conversion as a single relatively high speed converter converting the entire signal with little, if any, compromise in fidelity.
  • [0014]
    The means for decomposing the signal into a number of signal segments and the means for combining the processed signal segments to form the composite signal can include any number of suitable signal decomposing or combining devices (e.g., filters, analog circuitry, computer software, digital circuitry and optical filters). Preferably, a plurality or bank of analog or digital analysis filters is used to perform signal decomposition and a plurality or bank of analog or digital synthesis filters is used to perform signal reconstruction. The analysis and synthesis filters can be implemented in any number of ways depending upon the type of signal to be filtered. Filtration can be by, for example, analog, digital, acoustic, and optical filtering methods. By way of example, the filters can be designed as simple delays or very sophisticated filters with complex amplitude and phase responses.
  • [0015]
    In a preferred configuration, a plurality or bank of analysis and/or synthesis filters, preferably designed for perfect reconstruction, is used to process the signal segments. As will be appreciated perfect reconstruction occurs when the composite signal, or output of the synthesis filter bank, is simply a delayed version of the source signal.
  • [0016]
    In one configuration, the analysis filters and synthesis filters are represented in a special form known as the Polyphase representation. In this form, Noble identities are can be used to losslessly move the decimators to the left of the analysis filters and the interpolators to the right of the synthesis filters.
  • [0017]
    In another configuration, noise components in each of the signal segments can be removed prior to signal analysis or conversion in the processing step. The removal of noise prior to analog-to-digital conversion can provide significant additional reductions in computational requirements.
  • [0018]
    In yet another configuration, a coded signal is acquired rapidly using the above-referenced invention. In the processing step, the signal segments are correlated with a corresponding plurality of replicated signals to provide a corresponding plurality of correlation functions defining a plurality of peaks; an amplitude, time delay, and phase delay are determined for at least a portion of the plurality of peaks; and at least a portion of the signal defined by the signal segments is realigned and scaled based on one or more of the amplitude, time delay, and phase delay for each of the plurality of peaks.
  • [0019]
    In another embodiment, a method is provided for reducing noise in a signal expressed by a random or pseudorandom waveform. The method includes the steps of decomposing the signal into a plurality of signal segments and removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments. The means for decomposing the signal can be any of the devices noted above, and the means for removing the noise component includes a noise reducing quantizer, noise filters and rank reduction. Signal reconstruction may or may not be used to process further the processed signal segments. This embodiment is particularly useful in acquiring analog signals.
  • [0020]
    In yet a further embodiment, a method is provided for combining a plurality of signal segments (which may or may not be produced by analysis filters). In the method, synthesis filtering is performed on each of the plurality of signal segments. The means for performing synthesis filtering can be any of the devices noted above.
  • [0021]
    A number of differing system configurations can incorporate the synthesis filtering means in this embodiment of the invention. For example, a system can include, in addition to the synthesis filtering means, means for emitting the plurality of signal segments from a plurality of signal sources (e.g., antennas); means for receiving each of the plurality of signal segments (e.g., antennas); and means for converting each of the signal segments from analog format to digital format (e.g., analog-to-digital converter).
  • [0022]
    In another configuration, the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of digital-to-analog conversion devices for converting the plurality of decomposed signal segments from digital into analog format to form a corresponding plurality of analog signal segments; a plurality of amplifiers to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
  • [0023]
    In yet another configuration, the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of amplifiers to amplify the decomposed signal segments to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
  • [0024]
    In another embodiment, a method is provided in which digital signals are decomposed, processed, and then recombined. Signal processing can include signal correlation (e.g., signal modulation or demodulation), and oblique projection filtration (e.g., as described in copending U.S. Patent Application Ser. No. 08/916,884 filed Aug. 22, 1997, entitled “RAKE Receiver For Spread Spectrum Signal Demodulation,” which is incorporated herein fully by reference).
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • [0025]
    [0025]FIG. 1 depicts a first embodiment of the present invention;
  • [0026]
    [0026]FIG. 2 depicts an analog signal;
  • [0027]
    [0027]FIG. 3 depicts the analog signal of FIG. 2 divided up into a plurality of signal segments;
  • [0028]
    [0028]FIG. 4 depicts the first embodiment including decimation;
  • [0029]
    [0029]FIGS. 5A and 5B depict noble identities;
  • [0030]
    [0030]FIG. 6 depicts a polyphase filter representation;
  • [0031]
    [0031]FIG. 7 depicts a polyphase filter representation with noble identities;
  • [0032]
    [0032]FIG. 8 depicts another embodiment of the present invention;
  • [0033]
    [0033]FIG. 9 depicts the quantization process of the quantizers in FIG. 8;
  • [0034]
    [0034]FIG. 10 depicts a subband digital transmitter;
  • [0035]
    [0035]FIG. 11 depicts a subband analog transmitter;
  • [0036]
    [0036]FIG. 12 depicts a subband receiver;
  • [0037]
    [0037]FIG. 13 depicts rank reduction for noise filtering;
  • [0038]
    [0038]FIG. 14 depicts another embodiment of the present invention;
  • [0039]
    [0039]FIG. 15 depicts another embodiment of the present invention;
  • [0040]
    [0040]FIG. 16 depicts RAKE processing;
  • [0041]
    [0041]FIG. 17 depicts a multiplexed radar transmitter architecture;
  • [0042]
    [0042]FIG. 18 depicts a radar receiver architecture;
  • [0043]
    [0043]FIG. 19 depicts a digital communications example of a recursive, adaptive Wiener filter;
  • [0044]
    [0044]FIG. 20 depicts an alternative RAKE processing methodology; and
  • [0045]
    [0045]FIG. 21 depicts a least squares, multiple input multiple output filter design problem.
  • DETAILED DESCRIPTION
  • [0046]
    Referring to FIG. 1, an embodiment of the present invention is illustrated. As can be seen from FIGS. 1 and 2, a wideband, pseudorandom or random signal 40 (shown in FIG. 2) is passed to a bank or plurality of analysis filters 44 a-n. The signal 40 has a frequency band or domain, Fs, having frequency bounds, fo, (lower) and fn, (upper), and therefore a bandwidth of fo-fn (FIG. 2). The bandwidth commonly is at least about 1 kHz, more commonly at least about 1 GHz. Each of the analysis filters 44 a-n pass only a portion of the frequency band of the signal to form a plurality of subband signals 48 a-n, or time frequency components, characterized by discrete portions of the frequency band, Fs, of the signal 40 (FIG. 3). As will be appreciated, the summation of the individual frequency bandwidths of all of the subband signals 48 a-n is substantially the same as the bandwidth of the signal 40 (FIG. 3). The various subband signals 48 a-n are processed 52 a-n independently as described below to form a corresponding plurality of processed signal segments 56 a-n. The processed signal segments 56 a-n are passed to a bank or plurality of synthesis filters 60 a-n and combined to form a composite signal 64. Generally, the signal 40 is analog or digital and, when the signal 40 is analog, the composite signal 64 is digital, and, when the signal 40 is digital, the composite signal 64 is analog.
  • [0047]
    The analysis and synthesis filters 44 a-n and 60 a-n can be in any of a number of configurations provided that the filters pass only discrete, or at most only slightly overlapping, portions of the frequency domain of the signal 40. It is preferred that the frequency bands of the subband signals overlap as little as possible. Preferably, no more than about 5% and more preferably no more than about 1% of the frequency bands of adjacent subband signals overlap.
  • [0048]
    The filters can be analog or digital depending on the type of signal 40 or the processed signal segments 56 a-n. Examples of suitable analog analysis and synthesis filters include a suitably configured bandpass filter formed by one or more low pass filters, one or more high pass filters, a combination of band reject and low pass filters, a combination of band reject and high pass filters, or one or more band reject filters. Digital analysis and synthesis filters are typically defined by software architecture that provides the desired filter response.
  • [0049]
    In a preferred configuration shown in FIG. 4, the signal 40 is decomposed by the analysis filter bank 46 (which includes analog or digital analysis filters Hk(z) 44 a-n) into subband signals which are each sampled by a downsampler 64 a-n performing an M-fold decimation (i.e., taking every Mth sample), and the sampled subband signals are further sampled after signal processing by an up-sampler 68 a-n (and/or expander (which fills in L-1 zeros in between each sample)) and the further sampled subband signals are combined by a synthesis filter bank 62 (that includes analog or digital synthesis filters Gk(z) 60 a-n). The sampled subband signals, denoted by x0(n), x1(n), . . . xm−1(n), are the outputs of the N-band analysis filter bank and the inputs to the N-band synthesis filter bank. As a result of decimation, the subband signals are 1/N the rate of the input rate of the signal 40.
  • [0050]
    Preferably, the analysis and synthesis filters are perfect reconstruction filters such that the composite signal 64 is a delayed version of the signal 40 (i.e., y(n)=u(n−L) where y(n) is the composite signal, u(n) is the signal, and L is time of delay). Using perfect reconstruction filters, the subband signals 48 a-n can be downsampled without any loss in fidelity of the output signal. This downsampling is permissible because the subband signals are of narrow bandwidth and the consequence of the downsampling is that any processing application 52 a-n that is embedded in the subbands can run at significantly reduced rates.
  • [0051]
    As will be appreciated, a perfect reconstruction filter system can be formed by a number of different methods, including quadrature mirror filter techniques. A preferred technique for designing a filter bank is known as a least squares multiple input multiple output filter design notation. According to this technique, which is illustrated in FIG. 21, a rational transfer matrix defining one of the filter banks is known, i.e., either H(z) or GT(z), along with a rational transfer matrix F(z) defining the ideal output of the filter banks. Assuming that H(z) and F(z) are the known rational transfer matrices, the unknown rational transfer matrix, GT(z), is determined by the following equation:
  • G T(z)=[F(z) U T(Z −1)]+H0 −1(Z)
  • [0052]
    where
  • [0053]
    H(z)=H0(z)U(z); [H0(z) is the minimum phase equivalent of H(z)]
  • [0054]
    U(z)UT(z−1)=I; Paraunitary
  • [0055]
    [F(z)U(z−1)]x: Causal part of F(z)UT(z−1)
  • [0056]
    As will be appreciated if GT(z) were known and H(z) were unkown, then the equation would be solved for H(z) rather than GT(z), and GT(z) would be decomposed into the following:
  • GT(z)=Go T(z)U(z)
  • [0057]
    where
  • [0058]
    Go T(z) is the minimum phase equivalent of GT(z).
  • [0059]
    In a preferred embodiment, the rational transfer matrices of the analysis and/or synthesis filters are mathematically expressed in a polyphase filter representation. Exemplary equations defining the decomposition of the signal 40 by the analysis filters 44 a-n include the following: H ( z ) = l = 0 M - 1 z 1 E l ( z M )
    Figure US20010000660A1-20010503-M00001
  • [0060]
    where
  • [0061]
    M is the number of subbands (which is the same as the number of analysis filters in the analysis filter bank; l is the subband designation); E l ( z M ) = n = - e l ( n ) z - n e l ( n ) = h ( M n + l ) , 0 l M - 1
    Figure US20010000660A1-20010503-M00002
  • [0062]
    (known as a Type 1 polyphase filter representation) and H ( z ) = l = 0 M - 1 z - ( M - 1 - l ) R l ( z u )
    Figure US20010000660A1-20010503-M00003
  • [0063]
    where
  • Rl(zM)=EM−1−l(z)
  • [0064]
    (known as Type 2 polyphase filter representation). As will be appreciated, other techniques exist for expressing a rational transfer matrix defining a filter system including impluse response and filter description.
  • [0065]
    Noble identities can be used to losslessly move the decimators to the left of the analysis filters and the L-fold up-sampler and/or expander to the right of the synthesis filters. In this manner, the analysis and synthesis filters operate on lower rate data, thereby realizing significant computational savings. The noble identities include:
  • [0066]
    Identity I: Decimation by M followed by filtering defined by the mathematical function H(z) is equivalent to filtering by H(zM) followed by decimation by M (FIG. 5A).
  • [0067]
    Identity II: Filtering by G(z) followed by an upsampling by L is equivalent to upsampling by L followed by filtering by G(zL) (FIG. 5B).
  • [0068]
    By way of example, assume H(z) defines an order N finite impulse response (FIR) digital analysis filter with impulse response h(n), M=2, u(n) is the source signal and X(n) is the subband signal. Using the type 1 polyphase representation above, H(z) is decomposed to yield the following:
  • H(z)=H o(z 2)+H 1(z 2)
  • [0069]
    Based on the foregoing, FIG. 6 is a polyphase representation based implementation of H(z) without noble identities and FIG. 7 is a polyphase representation-based implementation of the analysis filters H(z) using noble identities to move the decimators ahead of the analysis filters. In this configuration, Ho(z2) and H1(z2) are FIR filters of order no+1 and n1+1, where N=no+n1+1. Ho(z2) and H1(z2) operate at half the rate as compared to H(z) and therefore have two units of time in which to perform all the necessary computations, and the components are continually active (i.e., there are no resting times). Accordingly, there is an M-fold reduction in the number of multiplications and additions per unit of time when using both polyphase representation and the noble identities to implement an M-fold decimation filter.
  • [0070]
    Subband signal processing can take a variety of forms. In one embodiment shown in FIG. 8 which depicts a receiver and antenna architecture, the source signal 40 and subband signals 48 a-n are in analog form and a plurality of quantizers or analog-to-digital converters are used to convert the subband signals 48 a-n to digital form before further processing 82 (e.g., correlation for encoded subband signals, subband signal digital beamforming in multiple antenna systems, etc.) and/or synthesis of the digital subband signals 78 a-n is performed. As noted above, the subband signals 48 a-n are preferably sampled by each of the decimators or downsamplers 64 a-n at a rate of at least about twice the bandwidth of the corresponding subband signal 48 a-n to maintain fidelity. As shown in FIG. 9, each quantizer, or analog-to-digital converter, 74 a-n determines the digital word or representation 90 a-n that corresponds to the bin 86 a-n having boundaries capturing the amplitude of the analog subband signal at that time and outputs the digital word or representation that represents the selected quantization level assigned to the respective bin. The digital subband signals 78 a-n are converted 94 a-n from radio frequency (RF) to base band frequency and optionally subjected to further signal processing 60. The processed subband signals 98 are formed into a digital composite signal 102 by the synthesis filter bank 60.
  • [0071]
    To provide increased accuracy, noise rejecting quantizers can be utilized as the quantizers 74 a-n. As will be appreciated, a noise rejecting quantizer assigns more bits to the portions of the subband signal having less noise (and therefore more signal) and fewer bits to the noisy portion. This selective assignment is accomplished by adaptively moving the bin boundaries so as to narrow the bin width (thereby increasing quantization fidelity. An example of a design equation for a Lloyd-Max noise rejecting quantizer is as follows: t k = x k - 1 + x k 2 + δ 2 ( x k ) - δ 2 ( x k - 1 ) 2 ( x k - x k - 1 ) ; x k = e k - 1 2 δ 2 ( x k ) x k
    Figure US20010000660A1-20010503-M00004
  • [0072]
    where:
  • [0073]
    x is the signal to be quantized;
  • [0074]
    N is the number of quantization levels;
  • [0075]
    k is signal identifier;
  • [0076]
    σ is the noise covariance.
  • [0077]
    The mean squared quantization error (MSE) ξ2 is as follows: ξ 2 = E ( x - x ^ ) 2 = E x 2 + k = 0 N - 1 [ σ 2 ( x k ) + x k 2 - 2 x k e k ] P k
    Figure US20010000660A1-20010503-M00005
  • [0078]
    where:
  • [0079]
    {xk}o N−1 are the representation points;
  • [0080]
    {ck}o N−1 are the quantization bins;
  • [0081]
    {tk}o N−1 are the bin thresholds;
  • [0082]
    fy(y) is the probability density function of y;
  • [0083]
    y=x+n, where x is the signal component and n the noise component; e k = E x | y C k ] = 1 / P k t k t k + 1 E [ x | y = α ] fy ( α ) α ; and P k = P [ y C k ] = t k t k + 1 fy ( α ) α
    Figure US20010000660A1-20010503-M00006
  • [0084]
    The LM equations require that the bin thresholds be equidistant from the representation points and that each representation point be the conditional mean of x in the corresponding quantization bin. As will be appreciated, a Lloyd-Max (LM) quantizer substantially minimizes the mean squared error between the discrete approximation of the signal and its continuous representation.
  • [0085]
    The noise covariance, δ, can be estimated by linear mean squared error estimation techniques. Linear mean squared error estimates are characterized by the following equation:
  • {circumflex over (X)}=Ty=RxyRyy −1y
  • [0086]
    where T is the Wiener filter, Rxy is the cross covariance between x and y and Ryy is the covariance of y.
  • [0087]
    Rxy and Ryy are unknown and require estimation. A number of techniques can be used to estimate Rxy and Ryy, including an adaptive Wiener filter (e.g., using the linear mean squared algorithm), direct estimation, sample matrix inversion and a recursive, adaptive Wiener filter, with a recursive, adaptive Wiener filter being more preferred.
  • [0088]
    The recursive, adaptive Wiener filter is explained in Thomas, J. K., Canonical Correlations and Adaptive Subspace Filtering, Ph.D Dissertation, University of Colorado Boulder, Department of Electrical and Compute Engineering, pp.1-110, June 1996. which is incorporated herein by reference in its entirety. In a recursive, adaptive Wiener filter assume {circumflex over (T)}M denotes the filter when M measurements of X and Y are used. Then {circumflex over (T)}M is the adaptive Wiener filter
  • TM=XMYM*(YMYM*)−1={circumflex over (R)}xy{circumflex over (R)}yy −1,
  • XM=[x1x2 . . . xM]; XM=[xMx]
  • YM=[y1y2 . . . yM]; YM=[yMy]
  • [0089]
    If another measurement of x and y is taken, and one more column is added to XM and YM to build {circumflex over (T)}M−1:
  • {circumflex over (T)} M+1 =X M Y M *{circumflex over (R)} M+1 −1 +xy*{circumflex over (R)} M−1 −1
  • [0090]
    The estimate of M+1 is {circumflex over (X)}M+1
  • {circumflex over (X)}M+1={circumflex over (T)}M+1YM+1
  • [0091]
    Using the estimate of XM+1, one can read off {circumflex over (x)}M+1, which is the estimate of x: x ^ M + 1 = 1 1 + r 2 x ~ M + r 2 1 + r 2
    Figure US20010000660A1-20010503-M00007
  • [0092]
    where
  • [0093]
    r2=y*{circumflex over (R)}M −1y and {tilde over (x)}M+1={circumflex over (T)}My.
  • [0094]
    Based on the above, when one observes y, the best estimate of the unknown x is {tilde over (x)}, with corresponding estimation error {tilde over (E)}M+1 and covariance {tilde over (Q)}M+1. If the unknown x becomes available after a delay, then {tilde over (x)}M+1 can be updated to {circumflex over (x)}M+1 with error covariance {tilde over (E)}M+1 and covariance {tilde over (Q)}M+1. The two covariances are related by the following formula: Q ~ M + 1 = Q ^ M + 1 + r 2 1 + r 2 x x *
    Figure US20010000660A1-20010503-M00008
  • [0095]
    By way of example and as illustrated in FIG. 19, consider a digital communication application in which the modulation scheme involves transmitting x0 and x1 when bits 0 and 1 are to be sent. During the setup of the communication link, the transmitter sends a known bit sequence across the unknown channel. Let XM be the matrix of signals that correspond to the known bit sequence. The receiver observes YM, which is the channel filtered and noise corrupted version of XM. Since the receiver knows the bit pattern, and therefore XM, it is able to build {circumflex over (T)}M. Therefore we refer to XM and YM as the training set.
  • [0096]
    Once the communication link is established, the transmitter sends a signal x, which corresponds to a data bit. The receiver observes the corresponding y and uses it to estimate x using {circumflex over (T)}M:
  • {tilde over (x)}={circumflex over (T)}My
  • [0097]
    The receiver determines r2, cos2θ and sin2θ.
  • [0098]
    When cos2θ is approximately equal to 1, {tilde over (x)} is deemed to be a good estimate of x and is used to decide if a 1 or 0 was sent. If, however, cos2θ<<1, then the estimate {tilde over (x)} is scaled by cos2θ, as required by equation 14, before it is used to decide if a 1 or 0 was sent. Once the decision of 1 or 0 is made, the true x is known and can be used to build {tilde over (x)} as required by equation 14 above and as illustrated in FIG. 19. The x and y are also added to the training set to update {circumflex over (T)}M.
  • [0099]
    In another embodiment, the source signal 40 is digital and the analysis filters are therefore digital, signal processing is performed by a digital-to-analog converter, and the synthesis filters are analog. FIG. 10 depicts a subband digital transmitter according to this embodiment. The signal 100 is in digital format and is transmitted to a bank of analysis filters 104 a-n to form a plurality of digital subband signals 108 a-n; the digital subband signals 108 a-n are processed by digital-to-analog converters 112 a-n to form analog subband signals 116 a-n; the analog subband signals 116 a-n are amplified by amplifiers 120 a-n to form amplified subband signals 124 a-n; and the amplified subband signals 124 a-n transmitted via antennas 128 a-n.
  • [0100]
    In another embodiment shown in FIG. 11, a subband analog transmitter is depicted where the signal 140 is analog and not digital. The signal 140 is decomposed into a plurality of analog subband signals 144 a-n by analog analysis filters 148 a-n and the analog subband signals 144 a-n amplified by amplifiers 152 a-n, and the amplified subband signals transmitted by antennas 156 a-n.
  • [0101]
    In yet another embodiment shown in FIG. 12, a subband receiver is depicted that is compatible with the subband analog transmitter of FIG. 11. Referring to FIG. 12, a plurality of subband signals 160 a-n are received by a plurality of antennas 164 a-n, the received subband signals 168 a-n down converted from radio frequency to baseband frequency by down converters 172 a-n; the down converted subband signals 176 a-n which are in analog form are converted by quantizers 180 a-n from analog to digital format; and the digital subband signals 184 a-n combined by synthesis filters 188 a-n to form the digital composite signal 192.
  • [0102]
    In any of the above-described transmitter or receiver embodiments, when the subband signals are encoded waveforms such as Code Division Multiple Access (CDMA) or precision P(Y) GPS code signals, the subband signals can be encoded or decoded to realize computational savings. In a receiver, for example, the subband signals are correlated with a replica of the transmitted signal prior to detection. The correlation process can be performed before or after synthesis filtering or before conversion to digital (and therefore in analog) or after conversion to digital (and therefore in digital). The approach is particularly useful for the rapid, direct acquisition of wideband pseudorandom noise encoded waveforms, like CDMA type signals and the P(Y) GPS code, in a manner that is robust with respect to multipath effects and wide-band noise. Because the M-subband signals have narrow bandwidths and therefore can be searched at slower rates, correlation of the subband signals rather than the signal or the composite signal can be performed with over an M-fold reduction in computation and therefore reduce the individual component cost.
  • [0103]
    To provide further reductions in computational requirements, the number of subbands requiring correlation at any trial time and Doppler frequency can be reduced. The pseudorandom nature of the coded signals implies that a coded signal will only lie in certain known subbands at any given time. According to the rank-reduction principle and as illustrated by FIG. 13, subbands 200 a-j outside of the subbands 204 a-j containing the coded signal can be eliminated to reduce the effects of wide-band noise in the acquisition and/or tracking of pseudorandom signals. This is accomplished by eliminating any subband in which the noise component exceeds the signal component (i.e., the SNR is less than 1). Such an elimination increases the bias squared, which is the power of the signal components that are eliminated, while drastically decreasing the variance, which is the power of the noise that was eliminated. In this manner, the mean squared error between the computed correlation function and the noise-free version of the correlation function is significantly reduced.
  • [0104]
    As shown in FIG. 14 to perform the correlation in the subband signals in GPS, CDMA, and other pseudorandom or random waveform applications, the replicated code 208 from the code generator 212 must be passed through an analysis filter bank 216 that is identical to the analysis filter bank 220 used to decompose the signal 224. Because the correlation must be performed for different segments of the replicated code 208, each indexed by some start time, this decomposition is necessary for all trial segments of the replicated code 208. A plurality of subband correlators 228 a-n receive both the subband signals 232 a-n and the replicated subband signals 236 a-n and generate a plurality of subband correlation signals 240 a-n. The subband correlation signals 240 a-n are provided by the following equation: q m , n ( i ) ( j ) = k = 1 N x m ( k + j ) p n ( i ) ( k )
    Figure US20010000660A1-20010503-M00009
  • [0105]
    where:
  • [0106]
    q(k) is the subband correlation signal;
  • [0107]
    pn (i)(k) is the component of the ith trial segment of the P(Y) code in the nth subband;
  • [0108]
    xm(k) is the component of the measurement that lies in the mth subband;
  • [0109]
    N is the number of samples over which the correlation is performed.
  • [0110]
    The subband correlation signals 240 a-n are upsampled and interpolated by the synthesis filters 244 a-n and then squared and combined. The resulting composite signal 248 is the correlation function that can be further processed and detected.
  • [0111]
    After the subband correlation signals 240 a-n are generated, the signals, for example, can be processed by a RAKE processor, which is commonly a maximal SNR combiner, to align in both time and phase multipath signals before detection and thereby provide improved signal-to-noise ratios and detection performance. As will be appreciated, a signal can be fragmented and arrive at a receiver via multiple paths (i.e., multipath signals) due to reflections from other objects, particularly in urban areas. The formation of a number of multipath signals from a source signal can degrade the correlation peaks, which contributes to the degradation of the detections. The RAKE processor determines the time and phase delays of these multipath signals by searching for correlation peaks in the correlation function and identifying the time and phase delays for each of the peaks. The RAKE processor then uses the time and phase delay estimates to realign the multipath signals so that they can add constructively and enhance the correlation peaks. The peak enhancement improves detection because of the increase in signal-to-noise ratio.
  • [0112]
    [0112]FIG. 15 depicts an embodiment of a signal processing architecture incorporating these features. Referring to FIG. 11, the signals 300 are received by one or more antennas 304, down converted by a down converter 308 to intermediate frequency, filtered by one or more filters 312, and passed through an analog-to-digital converter 316 to form a digital signal 320. The digital signal 320 is passed through an analysis filter bank 324 to generate a plurality of subband signals 328 a-n, and the subband signals 328 a-n to a plurality of subband correlators 332 a-n as noted above to form a plurality of subband correlation signals 336 a-n. The subband correlation signals 336 a-n are passed to a synthesis filter bank 340 to form a correlation function 344 corresponding to the signal 300. The correlation function 344 is passed to a pre-detector 348 to determine an estimated transmit time and frequency and an amplitude and delay for each of the correlation peaks. The estimated transmit time and frequency 352 are provided to a code generator 356 and the amplitude and time delay 360 associated with each correlation peak are provided to the RAKE processor 364. The code generator 356 determines a replicated code 368 corresponding to the signal 300 based on the estimated trial time and frequency. Using the correlation peak amplitudes and time and/or phase delays, the RAKE processor 364, as shown in FIG. 16, shifts the input sequence y(k) by the amounts of the multipath time and/or phase delays and then weights each shifted version by the amplitude of the peak of the correlation function corresponding to that peak to form a RAKED signal 372 (denoted by yR(k)). The RAKED sequence is commonly defined by the following mathematical equation: y R ( k ) = 1 i = 1 p A i i = 1 p A i - j φ i y ( k + t i )
    Figure US20010000660A1-20010503-M00010
  • [0113]
    where:
  • [0114]
    p is the number of multipath signals (and therefore number of peaks);
  • [0115]
    Ai is the amplitude of the ith peak;
  • [0116]
    ti is the time delay of the ith peak;
  • [0117]
    φ is the phase delay of the ith peak;
  • [0118]
    y(k) is the input sequence into the code correlator.
  • [0119]
    The RAKED signal 372 and the replicated code 368 are correlated in a correlator 376 to provide the actual transmit time and frequency 380 which are then used by detector 384 to detect the signal.
  • [0120]
    There are a number of variations of the above-desc system. The variations are useful in specific applicat such as GPS, CDMA, and radar.
  • [0121]
    In one variation of the system of FIG. 15 that i depicted in FIGS. 17-18, multiplexed radar transmitte receiver architectures are depicted. The radar signals 400 a-n are a number of coded waveforms that operate in separate, contiguous subbands (referred to as “radar su signals”). As shown in FIG. 17, the radar signals 40 are simultaneously transmitted by a plurality of transmitters 404 a-n that each include a plurality of analysis filters (not shown) to form the various radar subband signals 400 a-n. Referring to FIG. 18, the va radar subband signals 400 a-n are received by a signal receptor 410 and passed through a plurality of bandpass filters 414 a-n. A bandpass filter 414 a-n having unique bandpass characteristics corresponds to each of the radar subband signals. The various filtered subband signals 416 a-n are sampled by a plurality of decimators 422 a-n and quantized by a plurality of quantizers 426 a-n to form digital subband signals 430 a-n. The digital subband signals 430 a-n are analyzed by a plurality of detectors 434 a-n to form a corresponding plurality of detected signals 438 a-n. The detectors 434 a-n use a differently coded waveform for each of the transmitted radar subband signals 400 a-n so that the subband radar signals can be individually separated upon reception. As noted above in FIGS. 14-15, the coded radar waveform is decomposed by a plurality of analysis filters (not shown) that are identical to the analysis filters in the receiver to provide replicated subband signals to the detectors 434 a-n. Each detector 434 a-n correlates a radar subband signal 430 a-n with its corresponding replicated subband signal to form a plurality of corresponding detected signals 438 a-n. The detected signals 438 a-n are analyzed by a synthesis filter bank 412 a-n to form a composite radar signal 446.
  • [0122]
    In a variation of the system of FIG. 15, a bank of analysis filters and synthesis filters can be implemented both directly before and after the correlation step (not shown) to provide the above-noted reductions in computational requirements.
  • [0123]
    In another variation of the system of FIG. 15, the analysis filters can be relocated before the analog-to-digital converter 316 to form the subband signals before as opposed to after conversion.
  • [0124]
    In another variation shown of the system of FIG. 15 that is depicted in FIG. 20, the RAKE processor 364 can account for the relative delays in antenna outputs of the signal 300 (which is a function of the arrangement of the antennas as well as the angular location of the signal source) by summing the antenna outputs without compensating for the relative output delays. The correlation process may result in N×p peaks, where N is the number of antenna outputs and p is the number of multipath induced peaks. The Np peaks are then used to realign and scale the input data before summation. The RAKE 364 in effect has performed the phase-delay compensation usually done in beam-steering. The advantages of this approach compared to conventional beam steering techniques include that it is independent of antenna array geometries and steering vectors, it does not require iterative searches for directions as in LMS and its variants, and it is computationally very efficient. This approach is discussed in detail in copending application having Ser. No. 08/916,884, and filed on Aug. 21, 1997.
  • [0125]
    While various embodiments of the present invention have been described in detail, it is apparent that modifications and adaptations of those embodiments will occur to those skilled in the art. However, it is to be expressly understood that such modifications and adaptations are within the scope of the present invention, as set forth in the following claims.

Claims (37)

    What is claimed is:
  1. 1. A method for acquiring a signal having a bandwidth, comprising:
    decomposing the signal into a plurality of signal segments, each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
    processing each of the signal segments to form a plurality of processed signal segments; and
    combining the processed signal segments into a composite signal wherein the signal is one of analog or digital and the composite signal is the other one of analog or digital.
  2. 2. The method of
    claim 1
    , wherein the processing step includes performing analog-to-digital conversion of each of the signal segments.
  3. 3. The method of
    claim 1
    , wherein the processing step includes performing digital-to-analog conversion of each of the signal segments.
  4. 4. The method of
    claim 1
    , wherein the processing step includes removing a noise component from each of the signal segments to form a corresponding plurality of noise reduced signal segments and thereafter converting each of the noise reduced signal segments from one of analog or digital format to the other of analog or digital format.
  5. 5. The method of
    claim 1
    , wherein in the processing step each of the signal segments is processed separately.
  6. 6. The method of
    claim 1
    , wherein the composite signal has the same bandwidth as the signal bandwidth.
  7. 7. The method of
    claim 1
    , wherein the composite signal is a time delayed replica of the signal.
  8. 8. The method of
    claim 1
    , wherein the signal has a bandwidth of at least about 1 GHz.
  9. 9. The method of
    claim 1
    , wherein the sum of the plurality of signal bandwidths is equivalent to the signal bandwidth.
  10. 10. The method of
    claim 1
    , wherein the signal is in one of analog or digital format and the composite signal is in the other of analog or digital format.
  11. 11. The method of
    claim 1
    , wherein the processing step comprises:
    assigning boundary values to a plurality of bins;
    sampling a signal segment to provide a sampled value corresponding to the sampled portion of the signal segment;
    comparing the sampled value with assigned boundary values for each of the plurality of bins;
    selecting an appropriate bin for the sampled portion of the signal segment;
    thereafter reassigning new boundary values to at least a portion of the plurality of bins; and
    repeating the assigning, sampling, comparing and selecting steps.
  12. 12. The method of
    claim 1
    , wherein the processing step comprises:
    correlating the plurality of signal segments with a corresponding plurality of replicated signal segments to provide a corresponding plurality of correlation functions.
  13. 13. The method of
    claim 12
    , wherein the processing step comprises:
    determining an amplitude, time delay, and phase delay for at least a portion of a plurality of peaks defined by the plurality of correlation functions and realigning and scaling at least a portion of the signal defined by the signal segments based on one or more of the amplitude, time delay, and phase delay for the at least a portion of the plurality of peaks.
  14. 14. An apparatus for acquiring a signal having a signal bandwidth, comprising:
    means for receiving a signal in the form pseudorandom or random waveform having a signal bandwidth;
    means for decomposing the signal into a plurality of signal segments, each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
    means for processing each of the signal segments to form a plurality of processed signal segments; and
    means for combining the processed signal segments into a composite signal wherein the signal is one of analog or digital and the composite signal is the other one of analog or digital.
  15. 15. The apparatus of
    claim 14
    , wherein the means for processing includes means for performing analog-to-digital conversion of each of the signal segments.
  16. 16. The apparatus of
    claim 14
    , wherein the means for processing includes means for performing digital-to-analog conversion of each of the signal segments.
  17. 17. The apparatus of
    claim 14
    , wherein the means for decomposing is a plurality of low pass filters.
  18. 18. The apparatus of
    claim 14
    , wherein the means for decomposing includes a plurality of analysis filters and the means for combining includes a plurality of synthesis filters.
  19. 19. The apparatus of
    claim 14
    , wherein the means for combining is a perfect reconstruction filter bank.
  20. 20. The apparatus of
    claim 14
    , wherein the means for processing includes at least one of a plurality of analog-to-digital converters and a plurality of digital-to-analog converters.
  21. 21. The apparatus of
    claim 14
    , wherein the means for processing includes a noise rejecting quantizer.
  22. 22. A method for reducing noise in a signal having a bandwidth, comprising:
    decomposing the signal into a plurality of signal segments, each signal segment having a bandwidth that is less than the bandwidth of the signal and removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments.
  23. 23. The method of
    claim 22
    , further comprising:
    combining each of the processed signal segments to form a composite signal.
  24. 24. The method of
    claim 23
    , wherein the composite signal has the same bandwidth as the signal.
  25. 25. A system for reducing noise in a signal having a bandwidth, comprising:
    means for decomposing the signal into a plurality of signal segments, each signal segment having a bandwidth that is less than the bandwidth of the signal and means for removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments.
  26. 26. The system of
    claim 25
    , further comprising:
    means for combining each of the processed signal segments to form a composite signal.
  27. 27. The system of
    claim 26
    , wherein the composite signal has the same bandwidth as the signal.
  28. 28. A method for combining a plurality of signal segments having a signal bandwidth, to form a composite signal having a composite bandwidth, the frequency band of the composite signal including each of the signal segments, the method comprising:
    performing synthesis filtering on each of the plurality of signal segments to form the composite signal.
  29. 29. The method of
    claim 28
    , further comprising:
    emitting the plurality of signal segments from a plurality of signal sources and
    receiving each of the plurality of signal segments using a corresponding plurality of signal receptors.
  30. 30. The method of
    claim 28
    , further comprising:
    converting each of the signal segments from an analog format to a digital format.
  31. 31. A system for assembling a plurality of signal segments, each having a signal bandwidth to form a composite signal having a composite bandwidth that includes the frequency range of each of the signal segments, the system comprising:
    means for performing synthesis filtering on each of the plurality of signal segments to form the composite signal.
  32. 32. The system of
    claim 31
    , further comprising:
    means for emitting the plurality of signal segments from a plurality of signal sources and means for receiving each of the plurality of signal segments.
  33. 33. The system of
    claim 31
    , further comprising:
    means for converting each of the signal segments from an analog format to a digital format.
  34. 34. The system of
    claim 31
    , further comprising:
    a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments;
    a plurality of digital-to-analog conversion devices for converting the plurality of decomposed signal segments from digital into analog format to form a corresponding plurality of analog signal segments;
    a plurality of amplifiers to form a corresponding plurality of signal segments;
    a plurality of signal emitters for emitting the plurality of signal segments; and
    a plurality of receptors for receiving the plurality of signal segments.
  35. 35. The system of
    claim 31
    , further comprising:
    a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments;
    a plurality of amplifiers to amplify the decomposed signal segments to form a corresponding plurality of signal segments;
    a plurality of signal emitters for emitting the plurality of signal segments; and
    a plurality of receptors for receiving the plurality of signal segments.
  36. 36. The system of
    claim 31
    , further comprising:
    a plurality of receptors for receiving a plurality of analog signal segments;
    a plurality of analog-to-digital converters to convert the plurality of analog signal segments into the plurality of signal segments.
  37. 37. A method for processing an analog signal having a bandwidth, comprising:
    decomposing the analog signal into a plurality of analog signal segments, each analog signal segment having a signal segment bandwidth that is less than the signal bandwidth and
    processing each of the analog signal segments to form a plurality of processed analog signal segments; and
    combining the processed analog signal segments into a composite signal.
US09730316 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms Active US6380879B2 (en)

Priority Applications (5)

Application Number Priority Date Filing Date Title
US5622897 true 1997-08-21 1997-08-21
US5645597 true 1997-08-21 1997-08-21
US8703698 true 1998-05-28 1998-05-28
US09137383 US6252535B1 (en) 1997-08-21 1998-08-20 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09730316 US6380879B2 (en) 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US09730316 US6380879B2 (en) 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09995207 US6549151B1 (en) 1997-08-21 2001-11-26 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms

Publications (2)

Publication Number Publication Date
US20010000660A1 true true US20010000660A1 (en) 2001-05-03
US6380879B2 US6380879B2 (en) 2002-04-30

Family

ID=27368991

Family Applications (4)

Application Number Title Priority Date Filing Date
US09137383 Active US6252535B1 (en) 1997-08-21 1998-08-20 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09730330 Active US6362760B2 (en) 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09730316 Active US6380879B2 (en) 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09995207 Active US6549151B1 (en) 1997-08-21 2001-11-26 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms

Family Applications Before (2)

Application Number Title Priority Date Filing Date
US09137383 Active US6252535B1 (en) 1997-08-21 1998-08-20 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms
US09730330 Active US6362760B2 (en) 1997-08-21 2000-12-04 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms

Family Applications After (1)

Application Number Title Priority Date Filing Date
US09995207 Active US6549151B1 (en) 1997-08-21 2001-11-26 Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms

Country Status (3)

Country Link
US (4) US6252535B1 (en)
GB (1) GB2343801B (en)
WO (1) WO1999009650A1 (en)

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6392588B1 (en) * 2000-05-03 2002-05-21 Ramot University Authority For Applied Research & Industrial Development Ltd. Multifrequency signal structure for radar systems
US6400828B2 (en) * 1996-05-21 2002-06-04 Interval Research Corporation Canonical correlation analysis of image/control-point location coupling for the automatic location of control points
US20030033611A1 (en) * 2001-08-09 2003-02-13 Shapiro Jerome M. Embedded information modulation and demodulation using spectrum control orthogonal filter banks
WO2003100981A1 (en) * 2002-05-22 2003-12-04 Massachusetts Institute Of Technology High dynamic range analog-to-digital converter having parallel equalizers
US20040042557A1 (en) * 2002-08-29 2004-03-04 Kabel Allan M. Partial band reconstruction of frequency channelized filters
US20050031021A1 (en) * 2003-07-18 2005-02-10 David Baker Communications systems and methods
US20050050130A1 (en) * 2003-09-02 2005-03-03 Dabak Anand G. Ranging in multi-band OFDM communications systems
US20050111524A1 (en) * 2003-07-18 2005-05-26 David Baker Communications systems and methods
US20050239432A1 (en) * 2002-06-25 2005-10-27 Koninklijke Philips Electronics N.V. Ultra-wideband signal receiver using frequency sub-bands
US20060020428A1 (en) * 2002-12-03 2006-01-26 Qinetiq Limited Decorrelation of signals
US20090141775A1 (en) * 2005-02-25 2009-06-04 Data Fusion Corporation Mitigating interference in a signal
US20100017195A1 (en) * 2006-07-04 2010-01-21 Lars Villemoes Filter Unit and Method for Generating Subband Filter Impulse Responses

Families Citing this family (89)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6049770A (en) * 1996-05-21 2000-04-11 Matsushita Electric Industrial Co., Ltd. Video and voice signal processing apparatus and sound signal processing apparatus
US6947474B2 (en) 1996-08-23 2005-09-20 Tensorcomm, Inc. Rake receiver for spread spectrum signal demodulation
EP0999708A1 (en) * 1998-11-06 2000-05-10 TELEFONAKTIEBOLAGET L M ERICSSON (publ) Channel error correction apparatus and method
WO2000065372A3 (en) * 1999-04-27 2001-04-05 Champlain Brian De Single receiver wireless tracking system
FR2799073B1 (en) * 1999-09-29 2002-01-18 France Telecom Method for transmitting a signal BFDM / OQAM, processes of modulation and demodulation and corresponding device
US20050123080A1 (en) * 2002-11-15 2005-06-09 Narayan Anand P. Systems and methods for serial cancellation
US6466615B1 (en) * 1999-12-30 2002-10-15 Intel Corporation Delay locked loop based circuit for data communication
US6741650B1 (en) 2000-03-02 2004-05-25 Adc Telecommunications, Inc. Architecture for intermediate frequency encoder
US7146176B2 (en) 2000-06-13 2006-12-05 Shared Spectrum Company System and method for reuse of communications spectrum for fixed and mobile applications with efficient method to mitigate interference
DE10028593C1 (en) * 2000-06-14 2001-10-18 Daimler Chrysler Ag Digital/analogue signal conversion method uses transformation with orthogonal functions and determination of coefficients for re-conversion into analogue range
US6683567B2 (en) 2000-07-18 2004-01-27 Brian De Champlain Single receiver wireless tracking system
WO2002010689A1 (en) * 2000-08-02 2002-02-07 Continental Teves Ag & Co. Ohg Active magnetic field sensor, use thereof, method and device
US20050101277A1 (en) * 2001-11-19 2005-05-12 Narayan Anand P. Gain control for interference cancellation
US20040208238A1 (en) * 2002-06-25 2004-10-21 Thomas John K. Systems and methods for location estimation in spread spectrum communication systems
US7260506B2 (en) * 2001-11-19 2007-08-21 Tensorcomm, Inc. Orthogonalization and directional filtering
US7394879B2 (en) * 2001-11-19 2008-07-01 Tensorcomm, Inc. Systems and methods for parallel signal cancellation
US7076164B2 (en) * 2001-06-22 2006-07-11 Tellabs Operations, Inc. System and method for measuring power of optical signals carried over a fiber optic link
WO2003023444B1 (en) 2001-09-12 2003-06-19 Data Fusion Corp Gps near-far resistant receiver
US20030058148A1 (en) * 2001-09-21 2003-03-27 Sheen Timothy W. Multiple a-to-d converter scheme employing digital crossover filter
US8085889B1 (en) 2005-04-11 2011-12-27 Rambus Inc. Methods for managing alignment and latency in interference cancellation
US7577186B2 (en) * 2002-09-20 2009-08-18 Tensorcomm, Inc Interference matrix construction
US20050180364A1 (en) * 2002-09-20 2005-08-18 Vijay Nagarajan Construction of projection operators for interference cancellation
US7477710B2 (en) * 2004-01-23 2009-01-13 Tensorcomm, Inc Systems and methods for analog to digital conversion with a signal cancellation system of a receiver
US20050169354A1 (en) * 2004-01-23 2005-08-04 Olson Eric S. Systems and methods for searching interference canceled data
US7158559B2 (en) * 2002-01-15 2007-01-02 Tensor Comm, Inc. Serial cancellation receiver design for a coded signal processing engine
US6567030B1 (en) * 2002-02-27 2003-05-20 Lecroy Corporation Sample synthesis for matching digitizers in interleaved systems
US20030235252A1 (en) * 2002-06-19 2003-12-25 Jose Tellado Method and system of biasing a timing phase estimate of data segments of a received signal
US7787572B2 (en) * 2005-04-07 2010-08-31 Rambus Inc. Advanced signal processors for interference cancellation in baseband receivers
US7808937B2 (en) 2005-04-07 2010-10-05 Rambus, Inc. Variable interference cancellation technology for CDMA systems
US8761321B2 (en) * 2005-04-07 2014-06-24 Iii Holdings 1, Llc Optimal feedback weighting for soft-decision cancellers
US7876810B2 (en) * 2005-04-07 2011-01-25 Rambus Inc. Soft weighted interference cancellation for CDMA systems
US8005128B1 (en) 2003-09-23 2011-08-23 Rambus Inc. Methods for estimation and interference cancellation for signal processing
US7787518B2 (en) * 2002-09-23 2010-08-31 Rambus Inc. Method and apparatus for selectively applying interference cancellation in spread spectrum systems
US8179946B2 (en) * 2003-09-23 2012-05-15 Rambus Inc. Systems and methods for control of advanced receivers
WO2004036812A3 (en) * 2002-10-15 2004-07-15 Tensorcomm Inc Method and apparatus for channel amplitude estimation and interference vector construction
US7430253B2 (en) * 2002-10-15 2008-09-30 Tensorcomm, Inc Method and apparatus for interference suppression with efficient matrix inversion in a DS-CDMA system
US7711510B2 (en) 2002-10-24 2010-05-04 Lecroy Corporation Method of crossover region phase correction when summing signals in multiple frequency bands
US7957938B2 (en) * 2002-10-24 2011-06-07 Lecroy Corporation Method and apparatus for a high bandwidth oscilloscope utilizing multiple channel digital bandwidth interleaving
CN100583643C (en) * 2002-10-24 2010-01-20 勒克罗伊公司 Method and equipment for digitalized data signal
US7219037B2 (en) * 2002-10-24 2007-05-15 Lecroy Corporation High bandwidth oscilloscope
US20040146093A1 (en) * 2002-10-31 2004-07-29 Olson Eric S. Systems and methods for reducing interference in CDMA systems
US7541959B1 (en) * 2003-04-07 2009-06-02 Photonics Products, Inc. High speed signal processor
US6980147B2 (en) * 2003-04-07 2005-12-27 Photon Products, Inc. Channelized analog-to-digital converter
US7324036B2 (en) * 2003-05-12 2008-01-29 Hrl Laboratories, Llc Adaptive, intelligent transform-based analog to information converter method and system
US7409010B2 (en) * 2003-06-10 2008-08-05 Shared Spectrum Company Method and system for transmitting signals with reduced spurious emissions
JP3962785B2 (en) * 2003-07-02 2007-08-22 テクトロニクス・インターナショナル・セールス・ゲーエムベーハー Signal analyzer and the frequency domain data generating method
US7400692B2 (en) * 2004-01-14 2008-07-15 Interdigital Technology Corporation Telescoping window based equalization
US7460839B2 (en) 2004-07-19 2008-12-02 Purewave Networks, Inc. Non-simultaneous frequency diversity in radio communication systems
US7263335B2 (en) 2004-07-19 2007-08-28 Purewave Networks, Inc. Multi-connection, non-simultaneous frequency diversity in radio communication systems
US7253761B1 (en) * 2004-11-08 2007-08-07 United States Of America As Represented By The Secretary Of The Army Analog to digital conversion with signal expansion
US20060125689A1 (en) * 2004-12-10 2006-06-15 Narayan Anand P Interference cancellation in a receive diversity system
US20060229051A1 (en) * 2005-04-07 2006-10-12 Narayan Anand P Interference selection and cancellation for CDMA communications
US20060267811A1 (en) * 2005-05-24 2006-11-30 Kan Tan Method and apparatus for reconstructing signals from sub-band signals
US7463609B2 (en) * 2005-07-29 2008-12-09 Tensorcomm, Inc Interference cancellation within wireless transceivers
KR101184323B1 (en) * 2005-11-03 2012-09-19 삼성전자주식회사 Analog to digital conversion method and apparatus of receiver supporting software defined multi-standard radios
US7826516B2 (en) 2005-11-15 2010-11-02 Rambus Inc. Iterative interference canceller for wireless multiple-access systems with multiple receive antennas
US7345629B2 (en) * 2006-02-21 2008-03-18 Northrop Grumman Corporation Wideband active phased array antenna system
US8155649B2 (en) * 2006-05-12 2012-04-10 Shared Spectrum Company Method and system for classifying communication signals in a dynamic spectrum access system
US8326313B2 (en) * 2006-05-12 2012-12-04 Shared Spectrum Company Method and system for dynamic spectrum access using detection periods
US9538388B2 (en) * 2006-05-12 2017-01-03 Shared Spectrum Company Method and system for dynamic spectrum access
US7564816B2 (en) * 2006-05-12 2009-07-21 Shared Spectrum Company Method and system for determining spectrum availability within a network
US7304597B1 (en) * 2006-05-26 2007-12-04 Lecroy Corporation Adaptive interpolation for use in reducing signal spurs
US7633417B1 (en) * 2006-06-03 2009-12-15 Alcatel Lucent Device and method for enhancing the human perceptual quality of a multimedia signal
EP2049874B1 (en) * 2006-08-01 2010-11-17 Continental Teves AG & Co. oHG Sensor arrangement for the precise detection of relative movements between an encoder and a sensor
US8027249B2 (en) 2006-10-18 2011-09-27 Shared Spectrum Company Methods for using a detector to monitor and detect channel occupancy
US8997170B2 (en) * 2006-12-29 2015-03-31 Shared Spectrum Company Method and device for policy-based control of radio
US7474972B2 (en) * 2007-03-23 2009-01-06 Tektronix, Inc. Bandwidth multiplication for a test and measurement instrument using non-periodic functions for mixing
US8090052B2 (en) * 2007-03-29 2012-01-03 Intel Corporation Systems and methods for digital delayed array transmitter architecture with beam steering capability for high data rate
EP2151063B1 (en) 2007-05-25 2016-12-14 Nokia Technologies Oy Interference in communication devices
US7535394B2 (en) * 2007-07-10 2009-05-19 Lecroy Corporation High speed arbitrary waveform generator
US8055204B2 (en) 2007-08-15 2011-11-08 Shared Spectrum Company Methods for detecting and classifying signals transmitted over a radio frequency spectrum
US8184653B2 (en) * 2007-08-15 2012-05-22 Shared Spectrum Company Systems and methods for a cognitive radio having adaptable characteristics
GB0716942D0 (en) * 2007-08-31 2007-10-10 Agilent Technologies Inc Circuit for sample rate conversion
EP2319260A2 (en) * 2008-08-19 2011-05-11 Shared Spectrum Company Method and system for dynamic spectrum access using specialty detectors and improved networking
EP2369362A1 (en) * 2010-03-18 2011-09-28 Siemens Milltronics Process Instruments Inc. A receiver for a pulse-echo ranging system with digital polyphase decimation filter
US8669894B2 (en) * 2010-11-15 2014-03-11 Anpec Electronics Corporation Analog-to-digital converting method and functional device using the same
FR2968149B1 (en) * 2010-11-30 2013-03-15 Thales Sa Method and adaptive communications system in hf band
US8411791B2 (en) * 2011-01-14 2013-04-02 Broadcom Corporation Distortion and aliasing reduction for digital to analog conversion
US8659453B1 (en) * 2011-04-07 2014-02-25 Lockheed Martin Corporation Digital radio frequency memory utilizing time interleaved analog to digital converters and time interleaved digital to analog converters
US9432042B2 (en) 2011-05-26 2016-08-30 Tektronix, Inc. Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing
US8742749B2 (en) 2011-05-26 2014-06-03 Tektronix, Inc. Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing
US9306590B2 (en) 2011-05-26 2016-04-05 Tektronix, Inc. Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing
US9568503B2 (en) 2011-05-26 2017-02-14 Tektronix, Inc. Calibration for test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing
US8774308B2 (en) * 2011-11-01 2014-07-08 At&T Intellectual Property I, L.P. Method and apparatus for improving transmission of data on a bandwidth mismatched channel
US8781023B2 (en) 2011-11-01 2014-07-15 At&T Intellectual Property I, L.P. Method and apparatus for improving transmission of data on a bandwidth expanded channel
US9360577B2 (en) * 2012-01-31 2016-06-07 Cgg Services Sa Method and apparatus for processing seismic data
US20140163940A1 (en) * 2012-12-11 2014-06-12 David E. Erisman Method and system for modeling rf emissions occurring in a radio frequency band
DE102012025319A1 (en) * 2012-12-22 2014-06-26 Diehl Bgt Defence Gmbh & Co. Kg A method for processing a navigation satellite signal
US8928514B1 (en) 2013-09-13 2015-01-06 Tektronix, Inc. Harmonic time domain interleave to extend oscilloscope bandwidth and sample rate

Family Cites Families (57)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE610989C (en) 1930-07-01 1935-03-20 Gewerkschaft Wallram Cutter picks with carbide insert
DE558910C (en) 1931-02-06 1932-09-13 Beloit Iron Works Device for winding webs of paper
US4359738A (en) 1974-11-25 1982-11-16 The United States Of America As Represented By The Secretary Of The Navy Clutter and multipath suppressing sidelobe canceller antenna system
US5412391A (en) 1977-10-06 1995-05-02 The United States Of America As Represented By The Secretary Of The Navy Adaptive decorrelating sidelobe canceller
US4665401A (en) 1980-10-10 1987-05-12 Sperry Corporation Millimeter wave length guidance system
DE3343188A1 (en) 1982-12-01 1984-06-07 Tadiran Israel Elect Ind Ltd RF handling system
US4893316A (en) 1985-04-04 1990-01-09 Motorola, Inc. Digital radio frequency receiver
US4965732A (en) 1985-11-06 1990-10-23 The Board Of Trustees Of The Leland Stanford Junior University Methods and arrangements for signal reception and parameter estimation
DE3687748D1 (en) 1985-12-26 1993-03-25 Matsushita Electric Ind Co Ltd Uebertragungsmethode a digital signal with improved error rate characteristics in mehrweguebertragung.
US4694467A (en) 1986-07-03 1987-09-15 Signatron, Inc. Modem for use in multipath communication systems
FR2606237B1 (en) 1986-10-31 1988-12-09 Trt Telecom Radio Electr A band has analog crypto dynamic permutations
US4737713A (en) * 1986-11-26 1988-04-12 Fonar Corporation Apparatus and method for processing an electrical signal and increasing a signal-to-noise ratio thereof
US4922506A (en) 1988-01-11 1990-05-01 Sicom Corporation Compensating for distortion in a communication channel
US4933639A (en) 1989-02-13 1990-06-12 The Board Of Regents, The University Of Texas System Axis translator for magnetic resonance imaging
US5109390A (en) 1989-11-07 1992-04-28 Qualcomm Incorporated Diversity receiver in a cdma cellular telephone system
US5119401A (en) 1989-11-17 1992-06-02 Nec Corporation Decision feedback equalizer including forward part whose signal reference point is shiftable depending on channel response
EP0459383A3 (en) 1990-05-30 1993-12-15 Pioneer Electronic Corp Radio receiver
US5099493A (en) 1990-08-27 1992-03-24 Zeger-Abrams Incorporated Multiple signal receiver for direct sequence, code division multiple access, spread spectrum signals
JPH04123621A (en) * 1990-09-14 1992-04-23 Nippon Telegr & Teleph Corp <Ntt> Echo eraser
JP2906646B2 (en) * 1990-11-09 1999-06-21 松下電器産業株式会社 Audio sub-band coding apparatus
US5390207A (en) 1990-11-28 1995-02-14 Novatel Communications Ltd. Pseudorandom noise ranging receiver which compensates for multipath distortion by dynamically adjusting the time delay spacing between early and late correlators
JP3325890B2 (en) 1990-12-07 2002-09-17 クゥアルコム・インコーポレイテッド Cdma microcellular telephone system and distributed antenna system
US5513176A (en) 1990-12-07 1996-04-30 Qualcomm Incorporated Dual distributed antenna system
US5218619A (en) 1990-12-17 1993-06-08 Ericsson Ge Mobile Communications Holding, Inc. CDMA subtractive demodulation
US5151919A (en) 1990-12-17 1992-09-29 Ericsson-Ge Mobile Communications Holding Inc. Cdma subtractive demodulation
US5561667A (en) * 1991-06-21 1996-10-01 Gerlach; Karl R. Systolic multiple channel band-partitioned noise canceller
US5355533A (en) 1991-12-11 1994-10-11 Xetron Corporation Method and circuit for radio frequency signal detection and interference suppression
US5263191A (en) 1991-12-11 1993-11-16 Westinghouse Electric Corp. Method and circuit for processing and filtering signals
US5515378A (en) 1991-12-12 1996-05-07 Arraycomm, Inc. Spatial division multiple access wireless communication systems
DE4201439A1 (en) 1992-01-21 1993-07-22 Daimler Benz Ag High-rate data transmission procedure via digital radio channel - providing multipath propagation compensation by decision feedback equaliser of correctly phased and weighted antenna signal combination
CA2088082C (en) * 1992-02-07 1999-01-19 John Hartung Dynamic bit allocation for three-dimensional subband video coding
JPH05268128A (en) 1992-03-18 1993-10-15 Kokusai Denshin Denwa Co Ltd <Kdd> Cdma communication system
US5237586A (en) 1992-03-25 1993-08-17 Ericsson-Ge Mobile Communications Holding, Inc. Rake receiver with selective ray combining
GB2268364B (en) * 1992-06-25 1995-10-11 Roke Manor Research Improvements in or relating to radio communication systems
US5224122A (en) 1992-06-29 1993-06-29 Motorola, Inc. Method and apparatus for canceling spread-spectrum noise
JP2689823B2 (en) * 1992-07-21 1997-12-10 松下電器産業株式会社 Image signal reproducing apparatus and a disk device
US5289499A (en) 1992-12-29 1994-02-22 At&T Bell Laboratories Diversity for direct-sequence spread spectrum systems
JP3143247B2 (en) 1993-01-11 2001-03-07 沖電気工業株式会社 Code division multiple access demodulator
JPH0744473B2 (en) 1993-02-02 1995-05-15 日本電気株式会社 Demodulation system
US5353302A (en) 1993-02-03 1994-10-04 At&T Bell Laboratories Signal despreader for CDMA systems
US5305349A (en) 1993-04-29 1994-04-19 Ericsson Ge Mobile Communications Inc. Quantized coherent rake receiver
US5437055A (en) 1993-06-03 1995-07-25 Qualcomm Incorporated Antenna system for multipath diversity in an indoor microcellular communication system
US5442627A (en) 1993-06-24 1995-08-15 Qualcomm Incorporated Noncoherent receiver employing a dual-maxima metric generation process
GB9315845D0 (en) 1993-07-30 1993-09-15 Roke Manor Research Apparatus for use in equipment providing a digital radio link between a fixed and a mobile radio unit
DE4326843C2 (en) 1993-08-10 1997-11-20 Hirschmann Richard Gmbh Co Receiving method and receiver antenna system for eliminating multipath interference or control unit for carrying out this method
JPH0774687A (en) 1993-09-03 1995-03-17 Kokusai Denshin Denwa Co Ltd <Kdd> Diversity system
US5481570A (en) 1993-10-20 1996-01-02 At&T Corp. Block radio and adaptive arrays for wireless systems
US5386202A (en) 1993-11-03 1995-01-31 Sicom, Inc. Data communication modulation with managed intersymbol interference
DE4343959C2 (en) 1993-12-22 1996-04-25 Hirschmann Richard Gmbh Co Receiving method and receiver antenna system for eliminating multipath interference or control unit for carrying out this method
US5553098A (en) 1994-04-12 1996-09-03 Sicom, Inc. Demodulator with selectable coherent and differential data
US5440265A (en) 1994-09-14 1995-08-08 Sicom, Inc. Differential/coherent digital demodulator operating at multiple symbol points
US5568142A (en) 1994-10-20 1996-10-22 Massachusetts Institute Of Technology Hybrid filter bank analog/digital converter
US5602833A (en) 1994-12-19 1997-02-11 Qualcomm Incorporated Method and apparatus for using Walsh shift keying in a spread spectrum communication system
US5566167A (en) * 1995-01-04 1996-10-15 Lucent Technologies Inc. Subband echo canceler
US5561668A (en) * 1995-07-06 1996-10-01 Coherent Communications Systems Corp. Echo canceler with subband attenuation and noise injection control
US6430216B1 (en) * 1997-08-22 2002-08-06 Data Fusion Corporation Rake receiver for spread spectrum signal demodulation
US6177893B1 (en) 1998-09-15 2001-01-23 Scott R. Velazquez Parallel processing analog and digital converter

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6400828B2 (en) * 1996-05-21 2002-06-04 Interval Research Corporation Canonical correlation analysis of image/control-point location coupling for the automatic location of control points
US6628821B1 (en) 1996-05-21 2003-09-30 Interval Research Corporation Canonical correlation analysis of image/control-point location coupling for the automatic location of control points
US6392588B1 (en) * 2000-05-03 2002-05-21 Ramot University Authority For Applied Research & Industrial Development Ltd. Multifrequency signal structure for radar systems
US20030033611A1 (en) * 2001-08-09 2003-02-13 Shapiro Jerome M. Embedded information modulation and demodulation using spectrum control orthogonal filter banks
WO2003100981A1 (en) * 2002-05-22 2003-12-04 Massachusetts Institute Of Technology High dynamic range analog-to-digital converter having parallel equalizers
US20050239432A1 (en) * 2002-06-25 2005-10-27 Koninklijke Philips Electronics N.V. Ultra-wideband signal receiver using frequency sub-bands
US6792057B2 (en) * 2002-08-29 2004-09-14 Bae Systems Information And Electronic Systems Integration Inc Partial band reconstruction of frequency channelized filters
US20040042557A1 (en) * 2002-08-29 2004-03-04 Kabel Allan M. Partial band reconstruction of frequency channelized filters
US7299161B2 (en) * 2002-12-03 2007-11-20 Qinetiq Limited Decorrelation of signals
US20060020428A1 (en) * 2002-12-03 2006-01-26 Qinetiq Limited Decorrelation of signals
US20050031021A1 (en) * 2003-07-18 2005-02-10 David Baker Communications systems and methods
US7457350B2 (en) * 2003-07-18 2008-11-25 Artimi Ltd. Communications systems and methods
US20050111524A1 (en) * 2003-07-18 2005-05-26 David Baker Communications systems and methods
US20050050130A1 (en) * 2003-09-02 2005-03-03 Dabak Anand G. Ranging in multi-band OFDM communications systems
US20090141775A1 (en) * 2005-02-25 2009-06-04 Data Fusion Corporation Mitigating interference in a signal
US7626542B2 (en) 2005-02-25 2009-12-01 Data Fusion Corporation Mitigating interference in a signal
US20100017195A1 (en) * 2006-07-04 2010-01-21 Lars Villemoes Filter Unit and Method for Generating Subband Filter Impulse Responses
US8255212B2 (en) * 2006-07-04 2012-08-28 Dolby International Ab Filter compressor and method for manufacturing compressed subband filter impulse responses

Also Published As

Publication number Publication date Type
US6252535B1 (en) 2001-06-26 grant
US6549151B1 (en) 2003-04-15 grant
US6362760B2 (en) 2002-03-26 grant
WO1999009650A1 (en) 1999-02-25 application
GB0002745D0 (en) 2000-03-29 grant
GB2343801B (en) 2001-09-12 grant
US6380879B2 (en) 2002-04-30 grant
US20010000216A1 (en) 2001-04-12 application
GB2343801A (en) 2000-05-17 application

Similar Documents

Publication Publication Date Title
US5621730A (en) Multiple user digital receiver apparatus and method with time division multiplexing
US5894473A (en) Multiple access communications system and method using code and time division
US5831977A (en) Subtractive CDMA system with simultaneous subtraction in code space and direction-of-arrival space
US4313116A (en) Hybrid adaptive sidelobe canceling system
Miller et al. RFI suppression for ultra wideband radar
US7145972B2 (en) Polyphase channelization system
US6483867B1 (en) Tracking loop realization with adaptive filters
US6219376B1 (en) Apparatuses and methods of suppressing a narrow-band interference with a compensator and adjustment loops
US20040071200A1 (en) System for direct acquisition of received signals
US4734701A (en) Null processing receiver apparatus and method
US6239746B1 (en) Radiogoniometry method and device co-operating in transmission
US5874916A (en) Frequency selective TDOA/FDOA cross-correlation
US7430254B1 (en) Matched detector/channelizer with adaptive threshold
US6031882A (en) Adaptive equalization of multipath signals
US20020012411A1 (en) Global positioning system receiver capable of functioning in the presence of interference
US20130023225A1 (en) Selective-sampling receiver
US4403314A (en) Active detection system using simultaneous multiple transmissions
US6331837B1 (en) Spatial interferometry multiplexing in wireless communications
US7362799B1 (en) Method and apparatus for communication signal resolution
US5604503A (en) Multipath and co-channel signal preprocessor
US6624783B1 (en) Digital array stretch processor employing two delays
US5410750A (en) Interference suppressor for a radio receiver
US5991454A (en) Data compression for TDOA/DD location system
US20060154607A1 (en) System and method for estimating the multi-path delays in a signal using a spatially blind antenna array
US5822380A (en) Apparatus and method for joint channel estimation

Legal Events

Date Code Title Description
AS Assignment

Owner name: UNITED STATES AIR FORCE, OHIO

Free format text: CONFIRMATORY LICENSE;ASSIGNOR:DATA FUSION CORPORATION;REEL/FRAME:012077/0859

Effective date: 20010619

AS Assignment

Owner name: DATA FUSION CORPORATION, COLORADO

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KOBER, WOLFGANG;THOMAS, JOHN K.;REEL/FRAME:012358/0528

Effective date: 19980828

FPAY Fee payment

Year of fee payment: 4

FPAY Fee payment

Year of fee payment: 8

FPAY Fee payment

Year of fee payment: 12