ZA200804271B - Method for calculating of improved steering vectors - Google Patents
Method for calculating of improved steering vectors Download PDFInfo
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- ZA200804271B ZA200804271B ZA200804271A ZA200804271A ZA200804271B ZA 200804271 B ZA200804271 B ZA 200804271B ZA 200804271 A ZA200804271 A ZA 200804271A ZA 200804271 A ZA200804271 A ZA 200804271A ZA 200804271 B ZA200804271 B ZA 200804271B
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- 239000013598 vector Substances 0.000 title claims description 58
- 238000000034 method Methods 0.000 title claims description 32
- 239000011159 matrix material Substances 0.000 claims description 26
- 238000004364 calculation method Methods 0.000 claims description 17
- 230000008859 change Effects 0.000 claims description 3
- 230000015556 catabolic process Effects 0.000 claims description 2
- WWVKQTNONPWVEL-UHFFFAOYSA-N caffeic acid phenethyl ester Natural products C1=C(O)C(O)=CC=C1C=CC(=O)OCC1=CC=CC=C1 WWVKQTNONPWVEL-UHFFFAOYSA-N 0.000 claims 2
- SWUARLUWKZWEBQ-UHFFFAOYSA-N phenylethyl ester of caffeic acid Natural products C1=C(O)C(O)=CC=C1C=CC(=O)OCCC1=CC=CC=C1 SWUARLUWKZWEBQ-UHFFFAOYSA-N 0.000 claims 2
- 101150034533 ATIC gene Proteins 0.000 claims 1
- 238000001914 filtration Methods 0.000 description 8
- 230000003321 amplification Effects 0.000 description 6
- 238000003199 nucleic acid amplification method Methods 0.000 description 6
- 230000001629 suppression Effects 0.000 description 6
- 230000001427 coherent effect Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 230000003044 adaptive effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000003313 weakening effect Effects 0.000 description 2
- 238000007476 Maximum Likelihood Methods 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/0848—Joint weighting
- H04B7/0854—Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
Description
AN _ DE
DrG REF: 669914 : To ee
Method for calculation of improved steering vectors
- 5 The invention relates to a method for calculation of improved steering vectors.
More particularly, the invention relates to a method for determining the sensor characteristics of elements of an antenna array with an N channel broadband receiver at incidents of M signals Si...Sm by means of calculation of Steering-
Vectors for a signal Si with ke{1...M}. RE h
The filtering serves for amplification of a selected signal from a particular - ~ incident direction and/or the reduction of the remaining signals of a signal mixture from different incident directions. : REI
As example for a method for space selective filtering, which is required for determining the filter co-efficient of sensor characteristics of at least one of the incident signals, is known as “Signal Copy”“[1].
Hereinafter the modelling of the wave incidents known from [3], [5] is considered.
If the vector of the signals of the M incident flat waves at time t, at a reference point of the array of the N sensors is indicated by s(t), with x(t) the : vector of the complex sensor tensions measured at the time t, with A the : steering matrix and with n(t) the noise term, then the following applies:
X(t) = A-s(t) + n(t) (1) oo with A(8) = [a(61),...,a(6m)], N*M matrix of the sensor characteristics of the M signal incident directions 0 and a(6;) N-vector of the sensor characteristics for the i-th signal incident direction, hereafter also referred : to as “Steering Vector”.
. i 3 , -
Furthermore ~ R=E(x(t) - x*(t)) the sensor-covariance matrix (*(Star): hermitican) © S+E(s(t) - s*(t)) : the signal-covariance matrix
If for simplification sake it is assumed that the noise is time independent of
EE time, uncorrelated with the sensors and with the same output o® for all sensors, then : Sv
Q = E(n(t) - n"(t)) = ol the noise covariance matrix, whereby | is the unit matrix.
Under these conditions it follows that R
R = ASA” + ol | (2) : has a linear structure and positive real inherent values.
From the linear structure of (2) it follows that those N-M inherent values, which are orthogonal to the gaps of A, are all equal to the noise output o?. If : only one wave falls in with output o?, the associated inherent value Ew(1) =
BERT 61%. : The maximum Likelihood estimated value for the vector S(t) results from the equation (1) by: : . }
Sw(t) = (AHA) 2ARX(t) (3)
The product of the three matrixes is indicated also as pseudoinverse of the matrix A.
In a mixture of M signals from the m-th line of the pseudoinverse the vector with the complex filter co-efficient for amplification of the M signal and suppression of the remaining signals is received. In case of parallel processing with M measurement receptions thus simultaneously M signals can be processed. A special case of the signal copy procedure is present if merely one selected signal is amplified and no further signals are to be weakened. In this case reference is made to a “directional lobe”.
Only the knowledge of the steering vector for the incident directions of the signals is necessary for obtaining the filter according to equation (3).
Assumptions are taken such as according to the prior art for the sensor characteristics and therewith for the steering vectors of the signal incident : 5 directions. oo oo « idealised characteristics according to formulae (isotropic, radiator, short = dipole, small frame, etc). SE o with suitable characteristics calculated by computer programmes - : characteristics measured in the test field.
These assumed steering vectors deviate from the actual, e.g. as a result of a non-measured platform influence on the sensors, time variations, not exactly determined sensor positions, different cable lengths and suppressions, not ‘exactly determined directional values etc. Thereby the amplification of the “useful signal is deduced and as a result the sharp minimum in particular the weakening of the disturbance signal.
A stepwise improvement of the filter effect can be achieved by way of adaptive procedures (see for example [2]). In a Closed-Loop method the filter co-efficients are adapted continuously with the aid of a fed-in error signal.
The error at the output of the filter is led back into the adaptation algorithm. © Such methods are, however, complex and expensive. To this is to be added convergence problems [2]. Also for the application of adaptive methods, for : oo example the MVDR-Beamformer (Minimum Variance Distortionless Response) - [2] as a rule” the knowledge of the Steering-Vector of at least one signal is necessary. The knowledge of the remaining Steering-Vectors improves the convergence behaviour and the convergence speed.
Object of the invention is to suggest a method in order to determine from measured values of a direction plant exact Steering-Vectors and therewith in case of space selective signal filtering improved useful signal amplification and/or signal suppression.
- According to the invention, a method. for determining the sensor : characteristics of elements of an antenna array with an N channel broadband receiver at incidents of M signals S;...Sm by means of calculation of Steering-
Vectors for a signal Si with ke{1...M} includes the following method steps: a 5 ..- breakdown of the reception signals B into given time or frequency intervals, . allocation of stored measuring data, which is suitable for calculation of
Steering-Vectors for the reception signals broken down into the B time or frequency intervals, whereby for each of the B-time or frequency intervals ~ covariance matrixes Ci are formed from a time sequence of T measuring frames of the respectively N measuring signals of the broadband receiver, : allocation of a classification characteristic to the reception signals S;...Sm broken down into the B time or frequency intervals, ~ characterized thereby that oo for calculation of an improved Steering-Vector for a signal Sk in a first step a frequency interval F1 is selected, in which the signal Sy is the respectively : stronger signal and whereby the allocation to Sy takes place by way of pregiven classification characteristics or the correlation of Steering-Vectors obtained by means of stored measuring data, : and in a second step that time or frequency interval Bs is selected out of the frequency interval F1 allocated to a signal Sk which has the smallest deviation to a 1-wave case, whereby the Steering Vector for the signal Sy is placed equally to a gap of the covariance matrix C(1..N,1) of the time or frequency interval Bsk or alternatively equal to the inherent vector to the largest inherent value of the covariance matrix.
The covariance matrixes Cx may be calculated according to
T
Cik=z(ai(t)a*k(t)) t=1 with i,k = 1..N ak = complex value numbers of the FFT a,x = ~~ conjugated complex values numbers of the FFT. . From the B time or frequency intervals that time or. frequency interval Bsk may be selected, which provides the maximum quotient of the largest and second largest inherent value of the covariance matrix Ci.
From the B time or frequency intervals that time or frequency interval Bsx may be selected, which provides the maximum quotient from the largest inherent value and the sum of the positive inherent values of the covariance matrix Cg.
The classification characteristic may be a direction value, a signal level or a modulation type.
The Steering-Vectors applied for filter calculation in the fixed frequency operation may be formed of measuring values of different time intervals and during operation with frequency change or in frequency scan operation of measuring values in different frequency intervals and/or different time intervals. IE :
Accordingly by means of calculation of Steering-Vectors for a signal Sk with ke{1...M} the sensor characteristics of the elements of an antenna array with
N-channel broadband receiver with incidents of M signals S;...Sm are determined. The reception signals thereby are divided into B time or frequency intervals. Subsequently an allocation of saved measuring data takes place which is useful for calculation of Steering-Vectors, into the B time or frequency intervals reception signals, whereby for each of the B time or frequency intervals covariance matrixes Ci from a time sequence of T measuring frames of the respective N measuring signals of the broadband receiver are formed as well as allocation of a classification characteristic of the reception signals S;...Syw into the B time or frequency intevals.
,
For calculating an improved Steering-Vector for a signal Sk in a first step a frequency interval F1 is selected, in which the signal S¢ is the respective stronger signal and whereby the allocation to Six takes place by given oo classification characteristics or thé correlation of Steering-Vectors obtained by ~~ ~~ stored measuring data, and in a second step from frequency interval F1 allocated to the signal Sk such
E time or frequency sections Bex are selected, which show the smallest deviation . to a one-wave case, whereby the Steering-Vector for the signal Sy is equal to a gap of the Kovarianzmatrix C (1..N,1) of the time or frequency section Bg or alternatively equal to the own vector for the largest own value of the
Kovarianzmatrix. Lo | Co
The invention will now be described by way of example with reference to the accompanying schematic drawings. oo
In the drawings there is shown in:
Figure 1 a representation of a FIR-Filter in principle; - Figure 2 an example of an output signal of a space selective FIR-filter according to the state of the art;
B Figure 3 a schematic representation of a development plan for determining
S20 the incident direction of signals onto a sensor array;
Figure 4 a detailed representation of the development plan of the determination of Steering-Vectors in accordance with the invention; and
Figure 5 a comparison between the signal suppression by means of the known signal copy method and the method in accordance with the invention.
In a space selective FIR-Filtering (Finite Impulse Response-Filtering), such as for example with Signal-Copy the sensor signals measured by the N reception a _ 8 channels of a receiver are multiplied with complex filter co-efficients (that is used with particular amplitude and phase displacements) so that in the added signal as compared to the reception signal of an individual element an amplification in the direction of a useful signal and a weakening in the direction of disturbing signals is achieved (with reference to the accompanying
Figure 1, Figure 2). B
Figure 1 shows a space selective filtering with FIR-Filter: The input signals are linearly combined by way of the filter co-efficients. Figure 2 shows an example of the filter effect of ‘a space selective FIR-Filter. A (useful) signal from 10° azimuth is amplified, a (disturbing) signal from 80° azimuth is - weakened. The major lobe of the filter calculated with signal copy is relatively broad, whereas the minimum for the directions to be weakened is small and sharp. In undisturbed (noiseless) drop and at exactly known incident directions and sensor characteristics the minimum involves zero positions, that is the interference signals are completely tuned out. : Figure 3 shows a schematic representation of a development plan for determining the incident direction of signals onto a sensor array, whereby the method steps’ for determining the Steering-Vectors in accordance with the oo invention are series connected to a broadband direction finder with classifier.
In the N channel broadband receiver the electro-magnetic signal received from the coupled sensor array are converted analog/digital and are spectrally distributed by means of a Fast Fourier Transformation (FFT) to B Bins. Each :
FFT-Bin delivers complex value numbers a; with i-1..N. for a FFT-Frame : (measuring point), with Bin hereafter a frequency or time interval is considered.
A given number T of FFT-Frames is summed up for each Bin in a N*N covariance matrix C corresponding to.
T
Cik=Z(ai(t)a*(t)) withi,k = 1..N (4) t=1
. ~ In the next step the suitable signal number and directional values are found : for the covariance matrixes.
Suitable methods for estimation of signal number are, for example, the MDL
Principle (Minimum Description ‘Length-Principle)[3] for non-coherent signals and MDLC (Minimum Description Length coherent-principle) for coherent signals [4]. The directional value calculation can, for example, be for non- coherent signals by means of high resolution directional methods such as
MUSIC [5] and for coherent signals, e.g. performed with a Minimum-
Likelyhood estimator such as [5]. Signal number and incident directions can, however, also be available by way of other methods, such as for example histogramme evaluations with a 1-Wave Directional Procedure, for example conventional beam forming or by way of pre-knowledge of emitter locations. } Subsequently it is determined in which frequency interval the respective signals lie and to each signal a directional value is allocated. . In case of automatic design this can be determined by way of a classifier.
As starting point for the procedural steps given in the characterising part of claim 1 the following results must be available: oo ‘oe A measuring range split into frequency and/or time intervals (example : 20° splitting in frequency bins). eo For the signals detected in the frequency/time intervals at least one classification characteristic, such as directional value, level, modulation : type, etc must be allocated (for example directional value). oe To the signals detected in the frequency/time intervals stored measuring data must be allocated, from which Steering-Vectors can be determined (covariance matrixes).
The determination of the Steering-Vectors is performed subsequently in accordance with the invention corresponding to Figure 3 (dotted line box) and
Figure 4 as follows:
In the case of intended amplification of the (useful) signal 1 suitably from the total of the frequency bins of the directional finder only those frequency intervals F1 are selected, which contain the signals S;...Sm overlapping the signal 1. ~The determination of the suitable bins for determining the "Steering Vectors” takes place in two steps: oo e Allocation of the strongest signal contained in a bin to a signal Si from
S:...Sum based on a classification characteristic or by way of correlation of
Steering-Vectors. e Selection of the best suitable bin Bsk of all bins allocated to a signal Sy.
EE For signal allocation: CT
C0 The allocation takes place in the example corresponding to the classification characteristic directional value or in case of several directional values per bin corresponding to the directional value of the signal with the highest level
Co (level calculation e.g. according to [5]) of the signal of S;...Sw being closest in the space angle. If the angular distance to all signals is above a certain threshhold, then the bin is rejected.
Because for the series-switched directional value calculation as a rule already ~. assumptions regarding the antennae characteristics have been taken, that is for each signal Si of S;...Sm an assumed Steering-Vector a’ exist, then in oC place of the allocation by way of classification characteristics also an allocation by correlation of Steering-Vectors can be performed. For example, if in a
Steering-Vector sv determined in a bin is allocated to the signal Sy, if: ja’ conj(sv)>|a® conj(sv)]? with r=1..M and r not similar to k (conj: conjugated complex, scalar product) and | | oo (5) lal conj(sv)|?>> pregiven threshhold
For bin selection
The selection of the best suitable frequency bin Bg of all bins allocated to the signal Sy takes place by way of a criteria for determining a possibly clean 1 ~ wave case with least possible interference and noise. oo
A special embodiment of this condition using the inherent values of the sensor "correlation matrix R is described in the equation (6a, 6b):
In place of the inherent values of the usually not known sensor correlation 3 matrix R in equation (2), also as approximate the inherent values of the covariance matrix C summed by way of T measuring points in equation (4), can be used. For a signal Sk each bin is determined from the signal allocated to this bin, in which in the equation (6a) the represented relationship is a maximum. This relationship corresponds in the one wave case to the SNR (Signal to noise relationship). Equation (6b) thereby is an approximate for the equation (6a). ~~ Ew(1) with H=min(T,N) (6a)
SNR= H
YT Ew(2)
Cj=2 : - For T<N the matrix C has only T of zero different inherent values. Therefore it extends to the summation in denominator only upto H.
Ew) | (6b)
SNR= Ew(2) (H - 1) :
The Steering-Vector to the signal Si is obtained from a gap of the covariance matrix C(1..N,1) of the respectively allocated bin Bsc. Thereby in the i-th gap of the covariance matrix the Steering-Vector phases relate to the i-th sensor.
Alternatively, as Steering-Vector the inherent vector to the largest inherent value of the covariance matrix is used, which represents a solution of an average overall covariance matrix [5]. :
For signals, for which no such estimation of the Steering-Vector is available, because they are covered completely by strong signals, the Steering-Vector, assumed hitherto for example for direction, is retained. If no estimation or assumption regarding a Steering-Vector is available, then the associated signal is not considered in the filter calculation, that is neither amplified nor suppressed.
With the newly calculated Steering-Vectors the filter is calculated or brought up to date. Co
The Steering-Vectors can be determined, in addition to the described selection of suitable bins in the frequency region, also by way of a time interval. This is sensible in case of timely non-changed incidence directions, if for example . initially a covered signal is received later on with higher level than the remaining signals. In this case both frequency as well as time filictuations are utilised in the level relationship of the signals.
The threshhold values used in the algorithm are to be adapted corresponding to the stability of the signal situation.
In a special case of complete overlapping, if for example a weak signal is fully oo | covered ‘by a strong signal in the spectrum, then with more exact determination of the Steering-Vector of the stronger signal this can be amplified or suppressed during filtering.
In a special case of the use of a narrow band directional finder with fixed : adjusted medium frequency the determination of the Steering-Vectors of oo individual signals takes place by application of time sequential covariance matrixes. In such an operation with frequency change or in the frequency oo scan operation the frequency intervals also can be used analogously to the frequency bins of the broadband directional finder.
In Figure 5 by way of a measuring example the comparison between the signal suppression by means of the known signal copy method and the invention is represented. In the upper representation Figure 5 the receiving output of an individual dipole of a 9 element directional antenna with the incidents of 2 external signals by way of the bin number are shown. Signal 1° with about -90 dBm is around bin B 141, signal 2 with about -30 dBm is around bin 220. :
The medium representation shows the reception output according to application of signal copy according to equation 1 for amplifying the signal 1 and suppression of signal 2 to the signals of all elements of the directional
: a 13 antennae. Thereby for the individual dipole idealised circular antennae characteristics were assumed and phase differences corresponding to the geometric wave length of the wave extension. By means of these idealist
Steering-Vectors the direction values of both signals were determined and subsequently also the filter was calculated. The (useful) Signal 1 is amplified : ~ for about 10 dB, the (disturbing) signal 2 is reduced by about 10 dB.
The lower representation shows the filtering by means of signal copy and the - method in accordance with the invention for determining the sensor characteristics. The Steering-Vector of signal 1 is the covariance matrix for bin 141 and for signal 2 the covariance matrix for bin 220. The disturbance signal is suppressed for about 50 dB. The signal to interference ratio SIR improves itself in the example of the new method as compared to the individual dipole reception for about 60 dBm ‘and compared to the conventional signal copy method for about 40 dBm. BN oo
Literature
[1] Miller, M.I, Fuhrmann, D.R: “Maximum-Likelyhood Narrow-Band
Direction Finding and the EM Algorithm”, IEEE Transactions on ASSP,
Vol. 38, No. 9, September 1990 SE
[2] Godara, L.C.: “Smart Antennas”, CRC Press, Boca Raton, 2004
[3] Wax M., Kailath, T.: “Detection of Signals by Information Theoretic
Criteria”, IEEE ASSP, Vol. 33, No. 2, pp. 387-393, April 1985
[4] Wax M., Ziskind I.: “Detection the Number of Coherent Signals by the
MDL Principle”, IEEE Trans. ASSP, Vol. 37, pp. 1190-1196, August 1989
BET [5] R.O. Schmidt: “Multiple Emiter Location and Signal Parameter
Estimation”, IEEE Transactions on Antennas and Propagation, Vol AP-34,
No. 3, March 1986
Claims (7)
1. Method for determining the sensor characteristics of elements of an oo antenna array with an N channel broadband receiver at incidents of M signals S;...Sm by means of calculation of Steering-Vectors for a signal Sk with ke{1...M} including the following method steps: breakdown of the reception signals B into given time or frequency intervals, allocation of stored measuring data, which is suitable for calculation of Steering-Vectors for the reception signals broken down into the B time or frequency intervals, whereby for each of the B-time or frequency intervals covariance matrixes Ci are formed from a time sequence of T measuring frames of the respectively N measuring signals of the broadband receiver, allocation of a classification characteristic to the reception signals
S:...Sm broken down into the B time or frequency intervals, characterized thereby that for calculation of an improved Steering-Vector for a signal Sk in a first
~. step a frequency interval Fl is selected, in which the signal Sy is the respectively stronger signal and whereby the allocation to Sk takes place by way of pregiven classification characteristics or the correlation of ‘Steering-Vectors obtained by means of stored measuring data, and in a second step that time or frequency interval Bs is selected out of the frequency interval F1 allocated to a signal Sk which has the : ‘smallest deviation to a 1-wave case, whereby the Steering Vector for ~~ the signal Sy is placed equally to a gap of the covariance matrix
C(1..N,1) of the time or frequency interval Bs or alternatively equal to the inherent vector to the largest inherent value of the covariance matrix.
2. Method according to claim 1, characterized thereby that the covariance matrixes Ci are calculated according to T Cir=2(m(0a(t)
Co 16 EE ~ withi,k =1..N ak = complex value numbers of the FFT aik = conjugated complex values numbers of the FFT.
3. Method according to claim 2, characterized thereby that from the B time or frequency intervals that time or frequency interval Bs is selected, which provides the maximum quotient of the largest and second largest inherent value of the covariance matrix Ci.
= 4. Method according to claim 2, characterized thereby that from the B time = = or frequency intervals that time or frequency interval Bg is selected, oo which provides the maximum quotient from the largest inherent value and the sum of the positive inherent values of the covariance matrix Ci.
5. Method according to any one of the preceding claims, characterized thereby that the classification characteristic is a direction value, a signal "level or a modulation type.
6. Method according to any one of the preceding claims, characterized thereby that the -Steering-Vectors applied for filter calculation in the fixed frequency operation is formed of measuring values of different time intervals and during operation with frequency change or in frequency scan operation of measuring values in different frequency intervals and/or different time intervals.
i 17
7. ~ A method for determining the sensor characteristics of elements of an : antenna array substantially as hereinbefore described with reference to and as illustrated in the accompanying s atic drawings. Date: 15 May 2008 a oo "DR R OP GERNTHOLTZ DR GERNTHOLTZ INC : : Patent Attorneys of Applicant(s) POBoxS8. : oo : CAPE TOWN 8000 : oo 30 Union Road MILNERTON/CAPE 7441 SOUTH AFRICA Co Tel: (021) 551 2650 Telefax: (021) 551 2960 | g : ~~ DrG Ref:
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE200710023099 DE102007023099B4 (en) | 2007-05-16 | 2007-05-16 | Method for calculating improved steering vectors |
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| Publication Number | Publication Date |
|---|---|
| ZA200804271B true ZA200804271B (en) | 2009-03-25 |
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ID=39590215
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| ZA200804271A ZA200804271B (en) | 2007-05-16 | 2008-05-15 | Method for calculating of improved steering vectors |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP1993219B1 (en) |
| DE (1) | DE102007023099B4 (en) |
| ES (1) | ES2536510T3 (en) |
| ZA (1) | ZA200804271B (en) |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE3136625C1 (en) * | 1981-09-15 | 1983-03-31 | Standard Elektrik Lorenz Ag, 7000 Stuttgart | Wide-aperture direction finder |
| DE3523537C2 (en) * | 1985-07-02 | 1993-10-14 | Deutsche Aerospace | Method and receiving arrangement for suppressing inband interference |
| DE19803188B4 (en) * | 1998-01-28 | 2006-04-20 | Siemens Ag | Method and base station for data transmission in a radio communication system |
| DE102004017715A1 (en) * | 2004-04-10 | 2005-11-03 | Ewation Gmbh | Bearing method with FFT broadband sensor |
-
2007
- 2007-05-16 DE DE200710023099 patent/DE102007023099B4/en not_active Expired - Fee Related
-
2008
- 2008-04-04 ES ES08006845.5T patent/ES2536510T3/en active Active
- 2008-04-04 EP EP20080006845 patent/EP1993219B1/en not_active Not-in-force
- 2008-05-15 ZA ZA200804271A patent/ZA200804271B/en unknown
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| Publication number | Publication date |
|---|---|
| EP1993219B1 (en) | 2015-02-18 |
| DE102007023099B4 (en) | 2012-06-21 |
| EP1993219A3 (en) | 2012-05-16 |
| DE102007023099A1 (en) | 2008-11-27 |
| EP1993219A2 (en) | 2008-11-19 |
| ES2536510T3 (en) | 2015-05-26 |
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