`
`Nex‘t-generatlon plattorms will demand next—generation antenna performance. (TRW
`photo}
`
`_ A
`
`NTENNAS
`
`wk.
`30
`"u.
`1-
`
`u
`
`:Digitol Beomforming Basics
`
`Hons Steyskol
`
`ntenna performance is steadily
`
`Aincreasing as ever more sophis-
`
`ticated information is demanded
`
`from radar and communications sys-
`tems. Digital beamfonning (DEF) is a
`powerful technique for boosting anten—
`na performance. Beamforming in the
`strict sense corresponds to weighting
`and summing elemental signals. where-
`as digital beamfon'ning includes almost
`any spatial processing of digitized sig-
`nals from a sensor array. State-of—the-an
`microwave integrated Circuits. signal
`processing and high-speed digital elec—
`tronics are now beginning to make DBF
`feasible for microwave radar and com-
`
`munications. The importance of this
`technology will continue to grow. This
`paper describes general DBF concepts
`and early implementation.
`Each element of an array antenna re-
`ceives or transmits a signal. In the re-
`ceive mode. analog beamformers output
`the weighted sum of the sensor signals.
`reducing the signal dimensionality from
`the number of elements N to 1. Unlike
`
`analog beamfonners, DBF arrays digi—
`tize received signals at the element
`level. then process these signals in a
`special-purpose digital processor to
`form the desired beam. The total infor—
`
`mation available at the aperture is pre-
`served and is represented by the N indi-
`vidual element signals.
`Once the physical input signals have
`been properly digitimd. they can be ma-
`nipulated indefinitely. without incuning
`any further error since a digital repre-
`
`sentation of the signal is used rather
`than the real received signal power. As
`a result. any number of beams can be
`formed or the signal can be subjected to
`multiple hypotheses testing.
`
`DBF PROMISES
`
`Digital beamforming is applicable
`both on transmit and receive. although
`most of its advantages are realized in the
`receive mode. The most important ad-
`vantages are fast adaptive pattern
`nulling. super resolution and direction
`finding. antenna self—calibration and ul-
`tralow sidelohes. array element failure
`and pattern correction, closely spaced
`multiple beams. adaptive space-time
`processing and flexible radar power and
`time management. Many of these fea—
`tures have been addressed ineviously.M
`Adaptive space—time processing is a re-
`cently proposed technique5-5 for air-
`borne surveillance radars to suppress
`ground clutter that is spread over a large
`Doppler frequency band. DBF in the
`transmit mode may find its first applica-
`tion in cellular telephone networks.
`
`DBF IMPLEMENTATION
`
`A generic DBF array consists of an—
`tenna elements. receiver modules. ana—
`log-to—digital (AID) converters and a
`digital beamforrner and controller. as
`shown in Figure l. The simple ap-
`proach of dirt-telly sampling and digitiz—
`ing the incoming microwave signal is
`not yet practical because of digital hard-
`ware speed limitations. Therefore. the
`
`1
`
`so
`
`Page 1 of 6
`
`JOURNAL ol ELECTRONIC DEFENSE 0 JULY '96
`
`SAMSUNG EXHIBIT 1036
`
`Page 1 of 6
`
`SAMSUNG EXHIBIT 1036
`
`

`

`Xi
`
`DIGITAL
`
`
`BEAMFORMER
`
`wit xl'l
`
`
`
`BEAM
`
`
`CONTROLLER
`
`
`
`
`
`
`
`
`"'vgannversion. filtering and amplifying to a
`'.pawer level commensurate with the
`'
`'5 “3310 converter. as shown'In Figure 2.
`" Separate AID conversion of baseband 1
`F5"??-and Q signals allows a low sampling
`Ernie but requires channel matching IF
`sampling and digital UQ generation
`' {avoids this problem at the expense of a
`
`. Lhigber sampling rate. The equalizer
`:1. bumpensates for dispersion differences
`Eithetweert individual receivers. The
`
`'E‘downconversion can be done in one or
`.“i more steps which are governed by
`5 hardware considerations.
`-_
`.1
`After AID conversion. the signals
`‘ enter the actual digital beamfon'ner. a
`1{fast parallel processor that forms the
`winner product beams at a rate commen-
`'
`' with the signal bandwidth. typi-
`y in the MR: range for radar. The
`.‘eight vector(s) are derived from a sep-
`' beam controller. For open—loop
`- tive pattern control. the element sig-
`
`
`tails are also input to the beam controller
`that determines the proper weights via a
`suitable algorithm. This operation is per-
`fomned at the much slower rate of the
`
`external scenario change. typically on
`the order of a kill or less.
`
`FUNDAMENTAL SYSTEM
`CHARACTERISTICS
`
`Dynamic range and signal band-
`width are fundamental characteristics
`
`of microwave systems. In most cases.
`AID converters set these parameters
`for DBF arrays. For adaptive pattern
`nulling the beam controller character-
`istics are also important.
`Dynamic Range: The system‘s in—
`stantaneous dynamic range is deter-
`mined by the number of bits Nb of the
`ND converters and the number of
`
`parallel channels N. For a Gaussian
`signal. the upper limit is set by Nb and
`the lower limit by the quantization
`noise. leading to a dynamic range of
`approximately (6 Nb + [0 log N) dB.7
`Thus the range increases by 6 dB per
`hit, and the factor N expresses the
`gain arising from the coherent integra-
`tion of N element signals. AID con-
`verter nonlinearities may further re—
`strict the usable dynamic range.
`Signal Bandwidth: The signal
`bandwidth of the DBF system is de-
`termined by the AID converter sam-
`pling rate and by the beamformer pro-
`cessing. To digitize IF signals with
`components up to fm“. the Nyquist
`criterion requires an ideal sampling
`rate of f5 2 mex. whereas the same
`signals at baseband with analog I and
`Q channels can be sampled with two
`AID converters at a rate i5 2 fmu. In
`
`
`
`li’O GENERATOR
`
`Page 2 of 6
`
`JOURNAL of ELECTRONIC DEFENSE a JULY'KflE-i ‘
`.4.
`
`practice the signals must be slightly
`over sampled to provide a margin for
`realistic. finite slope filters.
`Despite modern computers‘ imprcs~
`sive performance. the processing re-
`quired by digital beamforrning may
`yet be challenging. With N elements.
`a beam requires N complex multiplies
`at the sampling rate (approximately
`B) that brings the total count to ap-
`proximately NB complex operations
`per sec (COPS), or about [03 COPS.
`with N = 100 and signal bandwidth B
`= 1 MHz. which poses no difficulties.
`However. this hypothetical set does
`not represent a full-scale radar. A full-
`scale radar may have several thousand
`elements and many independent
`beams. and this load is still challeng-
`ing. The processing cost becomes an
`implementation issue.
`As an alternative to farming custom
`beams with individual weight vectors.
`a fast Fourier Transform (FF'I') can be
`utilized to calculate the entire set of N
`
`orthogonal beams simultaneously. as—
`suming the array elements are uni-
`formly spaced. This approach is ex-
`tremely efficient and was only (bl/2)
`log: (Ni-N complex multiplies. How-
`ever. in application. the FFI‘ and the
`custom beams are not necessarily
`equivalent. The custom beams have
`arbitrary patterns and directions. and
`the FFI‘ beams have identical patterns
`and fixed angular spacing.
`The beam controller processing ca-
`pacity depends on the desired control
`algorithm. As a representative exam-
`ple. consider adaptive nulling via the
`sample matrix inversion (SMl)
`method. The formation of the sample
`matrix and its inversion take approxi-
`mately (W6) N3 complex operations.
`With N equal to approximately 100
`elements and an update rate of 100
`times/sec. this formation leads to ap-
`proximately 5 x 103 floating point op-
`erations (FLOPs). which is currently
`reasonable. However. for the more
`ambitious adaptive space-time pro-
`cessing envisioned for airborne sur-
`veillance radar. the number of spatial
`degrees of freedom is multiplied by
`the number of temporal degrees of
`freedom. in factor of three. In addition.
`the update rate needs to be increased.
`A factor of 10 is reasonable. This in-
`
`crease leads to processing loads on
`the order of I00 gigaFLOPs. which
`pose serious difficulties. Due to the
`N3 dependence. the number of adap-
`tive degrees of freedom clearly must
`be kept to an absolute minimum.
`
`r ll iN 9
`
`'
`
`Page 2 of 6
`
`

`

` .
`
`
`I nitrite
`Monrovia. CA 91016
`Tel: (313) 3599500. ext. 771
`Fax: (are) 3539100
`
`OTH ER IMPLEMENTATION
`ISSUES
`
`Its own program.
`
`A multitude of system concepts and
`IsRLICK are of interest aside from the ba—
`
`sics discussed previously. For instance.
`as til-1CD done in radar. the dynamic
`range may be extended by coherent in-
`legration in time. In effect. this exten-
`sion allows detection of signals smaller
`than the least significant bit because of
`the offset of the zero-mean noise volt-
`
`age. Based on this concept. an interest—
`ing radar has been proposed" with 4.000
`elements. 32-bit compression code and
`32 Doppler output cells. leading to 66-
`dB processing gain. With an operational
`dynamic range of 55 dB. the element
`signals are so far below the noise that a
`multibit AID converter seems unneces-
`
`sary. A 1-bit AID converter. which sim—
`ply outputs the plus/minus sign of the
`input signal. may be sufficient and
`would result in enormous All) convert—
`
`er and [F channel savings.
`Other computational simplifications
`may be gained by going from element
`space to beam space via a spatial
`Fourier transform. Assuming a scenar-
`io where there are signals only in a rel-
`atively small number of M directions.
`then only a correspondingly small
`number of beams needs to be consid-
`
`ered. rather than the large number of N
`elemental signals. In this case. process-
`ing those beams by an SMI or similar
`adaptive. algorithm requires on the
`order of M3 rather than N3 mathemati-
`
`cal operations. which usually dramati-
`cally reduces complexity. Sophisticat-
`ed adaptive systems based on this con~
`cept have been proposed."- "’
`
`DIGITAL BEAMFORMING AT
`HOME LABORATORY
`
`Early Activities
`
`Digital beamforrning has long been
`used in sonar systems and also for low-
`t'requency over—the-horizon radars.
`such as the Air Force East Coast Radar
`
`System (OTH-B). However. the data
`rates are much lower than required by
`modem microwave radars. Serious in—
`
`terest in employing DBF for such sys-
`tems was first stimulated in the US
`
`[0 years ago by a joint
`about
`DARPAJUS Army MICOM study. Its
`objectives were to chart potential tech-
`nical options offered by DBF tech—
`niques and to quantify the benefits de-
`rived from them in selected applica-
`tions. Rome Laboratory consulted on
`this study and at the same time started
`
`Hardware Developments and
`Experiments
`An early US Air Force program ad-
`dressed array calibration. a problem
`common to all DBF arrays. For this re;
`search. a 32-element linear array operat-
`ing at C—band was built with high-per—
`formance commercial components.“
`Triple conversion receivers provided
`analog l and Q signals that were digi-
`tized by a pair of l0»bit/O.5~MHz AID
`converters. The array featured a novel
`self-calibration system that injected an
`accurate pilot tone immediately behind
`each antenna element and thus moni-
`
`tored the 32 receive channels. Afler digi-
`tal correction of channel imbalances
`
`(fl-dB amplitude. random phase) and
`[IQ and DC-offset errors. the RMS
`phase error was 2". consistent with a -
`45-dB sidelobe level.
`
`Another. separate project was the
`technology demonstration of a fast digi-
`tal beamformer” with performance
`compatible with an actual radar system.
`This successful design has several
`unique features. Four parallel processors
`accept 64 complex digital input channels
`and form four independent inner product
`beams at a 20-MH2 clock rate. Since the
`
`bandwidth is excessive for many appli-
`cations. the design allows flexibility
`with respect to the number of beams
`formed. Thus. 4, 8. l6 or 3?. beams can
`be multiplexed with a proportionally re~
`duced bandwidth. The high computa-
`tional capacity. 5 x 109 complex multi-
`plies per sec. is achieved with a systolic
`processor architecture based on the qua-
`dratic residue number system. This
`number theoretic approach is highly ef-
`fective for multiplications and additions
`and uses integer arithmetic so that
`round-off errors are avoided. The finite
`
`dynamic range is tailored to conespond
`to the limited range of the quantized
`input signals. Compared to a conven-
`tional approach. this processor has about
`40% less complexity (defined as the
`product of gate count and gate delays).
`These two systems coupled with a
`beam controller (a general-purpose
`computer) form the major components
`of the RUIpswich antenna site real-
`time digital beamfonning testbed. This
`testbed was used to study adaptive pat-
`tern nulling and super resolution.
`Fast adaptive jammer suppression is
`presently the strongest drive for DBF.
`Analog systems are usually based on
`feedback loops and their convergence
`is scenario-dependent — and often
`
`JOURNAL oi ELECTRONIC DEFENSE 0 JULY '96
`
`CIRCLE 15
`
`Page 3 of 6
`
`Page 3 of 6
`
`

`

`slow. Digital open-loop systems need
`no feedback and are scenario-indepen-
`dent and significantly faster. The SM!
`algorithm was used to demonstrate
`open-loop adaptive nulling.
`Ajammer was placed at -10". the in—
`terference-plus-noise covariance mar
`trix was measured and the adapted
`weights were computed using a steer—
`ing vector for a desired—look direction
`at broadside with a 20-dB Taylor taper
`imposed. The array was then phase
`scanned and the received power was
`measured as a function of scan angle.
`as shown in Figure 3. This pattern rep-
`resents jammer power only. and ob-
`taining the adapted response in this
`way provides a direct measure of jam—
`mer cancellation. The main beam cor-
`
`responds to maximum received jam-
`mer power and the broadside null to
`
`jantmcr cancellation of 5‘) dB. which is
`the l'ull dynamic range of lllt.‘ systcin,
`The resultant adapted pattern docs
`not yield Ill—dB sidclohcs. vthich can
`he explained by an cigcnvdccomposi-
`tion of the covariance matrix It
`tilti-
`
`rnately depends upon the arm} errors
`if that is. the DC ot't‘sct. l/Q. third har-
`monic and even the differences be-
`
`tween the noise figures of the element
`receivers. '7‘
`
`Super-resolution and direction—lind-
`ing techniques aim to resolve sources
`closer than the Rayleigh limit. The key
`ties on the o prim'r' assumption that the
`received array signal vector is generated
`by a few point sources only. and then
`the corresponding spatial frequencies in
`this signal are determined with modem
`spectrum estimation methods. These
`methods involve nonlinear signal pro—
`
`ccwing. and thc .tlgtll'ill'll‘lh tend to he
`highly L‘tlllllllt.‘\.
`trial-ring a DBF array
`requisite for their practical implement-.17
`lion. An experiment using the well
`known multiple signal classification
`tNlUSICt algorithm was performed in
`“Inch two uncorrelated sources illumi-
`
`nated the array l‘roni directions that
`non: only l7" (approxiittately 0.4
`beantwidtht apart. The received signals
`were analyzed with this algorithm. The
`response is plotted in Figure 4. The
`sharp peaks correspond exactly to the
`directions of the two signals. For com-
`parison. the response is shown for the
`sources when scanned by a convention-
`al beam and a monopulse beam. respec-
`tively. Clearly. only the super-resolu-
`tion algorithm is able to resolve such
`closely spaced sources. and a sum beam
`or a monopulse beam fails completely.
`
`And Elsewhere in the World of
`Antenizlr Technology
`
`The theory assocratod .with‘DBF’s ability to manipulate
`the appearance and response of an antenna pattern seems
`almast mystical, but program is being made in translating
`the theory into practice. Sevaral DBF applications and
`hardware advances in several adjunct fields deserve spe~
`ciai recognition.
`Andrew SciCom'tn (Garland. TX) has developed vari-
`ous beamforming technologies for both military and
`commemia'i applications. An HF Digitally Adaptive
`Beamfonning subsystem15 a case in point. “this M an—
`tenna system is able to null up to M- I undesired (jam-
`ming) sign; and.thanabeam directed at a desired sig-
`nal Iocafioti. Thetypical system consists of four to as
`many as eightfantcnnasr Current activity is aimed at im-
`proving theneqnimd algorithms and transitioning to a
`VXI form factor. Wand UHF versions of the system
`are under consideration.
`Scientists at Roke Manor (Romsey, Hampshire. Eng-
`land), the research arm of Siemens Pleasey, have been
`involved in advanced antenna beamforming since the
`early 1970s. Digitally adaptive beamforming has been
`applied to the Multifunction Electronically Scanned
`Adaptive Radar (MESAR) developed in conjunction
`with the UK Defence Research Agency. The MESAR
`consists of some 1,000 $~band active phased-array ele-
`ments. While standard phase shifters provide electroni-
`cally controlled beam steering, each output is then com—
`blast! into one of 16 subarrays for adaptive beamform-
`ing. Each subway feeds its own receiver channel for
`conversion to digital I and Q basebands. The 16 HQ
`channels are adaptively beamformed using complex
`weight multipliers to provide protection against up to 15
`sidetobe or mainbeamgamers.
`
`5‘
`
`Page 4 of 6
`
`Siemens Plessey has also entered into a strategic alli-
`ance with the Watkins-Johnson Co. (Palo Alto. CA) to
`interface advanced communications digital receiver tech«
`nology into Roi-re Manor adaptive array processing and
`DBF algorithms. In this HF communications application,
`super-resolution DF processing provides improved read-
`ability in the direction of signal interest, while nulling
`other unwanted co-channel signals.
`The ability to genomic numerous antenna beams in ur-
`bitrary directions poses a challenge to measurement in-
`strumentation. Antenna patterns are generally measured
`with instrumentation receivers that measure the response
`of the antenna as a function of angle off boresight. Con-
`ventional antenna pattern receivers perform a few thou-
`sand measurements per see. For an antenna system capa-
`ble of synthesizing hundreds of thousands of dtferem pat-
`terns, however. the measurement time per pattern must be
`greatly reduced. To fill this need. the Aeroflex Lintek
`Corp. (Powell. OH) has produced the élan antenna-meas-
`urement system. The éian system is capable of collecting
`four million sampleslsec at frequencies from 100 MHZ to
`100 01-12. This increased measurement speed not only re-
`duces test time but in some cases can lead to new insights.
`such as a study of the time-varying response of an adap-
`tive DBF antenna as its pattern evolves.
`A portable kit of antennas intended for cellular tele—
`phone appiications in the Nordic 450. AMPS and TACS
`bands has been introduced by Electro~Mett~ics (John—
`stown, NY). Consisting of directional Yagis and omnidi-
`rectional antennas covering the 430- to 470-Ml-Iz and
`824- to 960-MHz range. along with required preampli—
`fiers. switch. filters and cables. the kit allows antennas to
`be assembled in the field without tools.
`
`—Don Herskavr'tz
`
`JOURNAL of ELECTRONIC DEFENSE U JULY '96
`
`Page 4 of 6
`
`

`

`Circular Array with Frequency-
`Invariant Pattern
`
`Circular array antennas have a
`unique capability. They can generate a
`main beam and sidelobcs that are e5-
`
`tentially independent of frequency be-
`cause the far field pattern can be repre—
`sented in terms of orthogonal phase
`modes (mode of unit amplitude/linear
`phase azimuth variation). So long as
`the relative amplitudes of these modes
`are constant. the entire pattern is con-
`stant with frequency. However. to gen-
`erale constant amplitudes. the required
`beamfonning network is complicated.
`For arrays with more than 32 elements.
`it becomes feasible only with DEF.”
`The basic pattern synthesis tech-
`nique has been given previously.” 0n
`receive. the N element signals are
`transformed into phase modes by an N
`X N Fourier transformer. which is fol-
`lowed hy in-line filters that remove the
`frequency dependence of the individ-
`ual phase modes. Finally. the ampli—
`tude and phase taper corresponding to
`the desired beam shape and look direc—
`tion are imposed. and the phase modes
`are summed to produce a frequency-in-
`variant pattern.
`The beamwidth is determined by the
`number of phase modes used in the
`pattern. For given numbers of elements
`N and phase modes M. the usable pat-
`tern bandwidth is roughly given by M
`<2ka (N. where its is the cylinder cir-
`cumference measured in wavelength.
`At the lower end. the patient becomes
`super directive. and at the upper end
`the element spacing exceeds half a
`wavelength. leading to pattern pertur-
`bations. The filter responses for the
`phase modes have to be determined
`corresponding to the actual array ele-
`ment pattern.
`To demonstrate the features of fre-
`
`quency-invariant patterns. a circular
`array was built with 64 elements com-
`posed of monopoles in a parallel-plate
`region. The electrical design was based
`on a theoretical analysis!“ that agreed
`
`c
`
`.-60
`
`POWER(as) asses
`
`20 40 BO 80
`
`£0 60 4o -20
`
`0
`6 i“)
`Fig. 3 Adaptive pattern nulllng wlth the SMI
`algorithm on the BL azelement array.
`
`well with measurements. The feeding
`network was simulated by sequentime
`switching one digital receiver to the
`array elements. recording patterns and
`forming the composite army patterns off
`line. Figure 5 shows three 30«dB
`Chebyshev patterns taken at 4. 5 and 6
`GHz. demonstrating stable nulls and no
`beam squint over a 40% bandwidth.
`This study showed that circular ar—
`rays with DBF can generals: high-quirk
`ity patterns. with narrow beams anti
`deep pattern nulls. that are stable over
`large bandwidth. These features are at-
`tractive for many applications. includ-
`ing adaptive pattern nuiling.
`
`Array Element Pattern
`Correction
`
`[n a small array. all elements have
`different radiation patterns because of
`mutual coupling. which may preclude
`precise pattern control. However, with
`DBF these adverse effects can be cor-
`
`tecwd.” Rome laboratory's method is
`based on the following observation: in
`the receive mode. the individual antenna
`element signal has several constituents.
`one dominant constituent resulting from
`the direct incident plane wave and sever-
`al lesser constituents resulting front scat-
`tering of the incident wave at neighbor-
`ing elements. These constituents can be
`resolved and scattering compensated for
`by linear transformation, which is ac-
`complished by a matrix multiplication
`performed on the element output sig-
`nals. The compensation is scan-indepen-
`dent; the matrix is fixed and applies for
`all desired patterns and scan directions.
`The theoretical technique has been veriv
`fied in a demonstration with an eight-
`element array. where the initial sidelobe
`level was reduced from 20 dB to 30 dB.
`as shown in Figure 6.
`
`—DlFFEfiENOE—- MUSIC —- SUII
`BEAII
`BEAM
`
`D
`
`.it 4“i.~35
`mnurunetda)ititaa.
`
`'80 -20 40
`
`o
`9 H
`
`Fig. 4 Super resolutlon with the MUSIC
`algorithm on the BL 32-element array.
`
`
`
`JOURNAL ofmm DWSE ' JULY '96
`
`Page 5 of 6
`
`Page 5 of 6
`
`

`

`o
`
`"3’, anE
`III
`
`3 ~40
`B.
`
`
`
`4:330
`
`«so
`
`a
`ANGLE (’1
`
`an
`
`130
`
`Fig. 5 Measured 30-db Chebyshev
`patterns at 4. 5 and 6 GHz. overlaid.
`
`— BEFORE CORRECTION
`—AFI'EH DDHRECTIDN
`-—-IDEAL PATI'EHN
`
`
`
`ital systems will realize more sophisti-
`cated control algorithms. With the
`spectacular advances in high-speed
`digital electronics. these systems may
`be here strum-r than anticipated.
`
`This article was adapted from “Digital Beam~
`forming at Rome Laboratory." Microwave
`Journal. February 1996. pp. 100426.
`
`
`
`
`
`50
`-30
`0
`30
`ANGLE ('l
`
`-60
`
`tenna. RADC—TR—BB-Ba. June 1988.
`12. L. Langston. S. Sanzglri and K.
`Hinman. at al.. Design Definition for a
`Digital Baamtorming Processor. RADC-
`TR-BB—BB. June 1938.
`13. W. Humbert and H. Steyskal, "A Fle-
`cent Evaluation of the Digital Beamiorm—
`lng Testbed at Rome Laboratory.‘ Home
`Lab.. TP-93-198. September 1993.
`14. H. Stayskal. 'Circular Array with
`Frequency-invariant Paitem." IEEE AP—
`S lntamational Symposium. San Jose.
`CA. June 1989.
`15. D.E.N. Davies. ”Circular Arrays.” in
`Hodge at al eds... The Handbook of An-
`tenna Design. Vol. 2. Peregrinus Ltd..
`UK. 1983.
`15. B. Tomasic. 'Circular Array cl
`CoaxialIy-lad Monopole Elements in a
`Parallel Plate Waveguide Experiment.
`Home Lab. TFl-85-243. December 1985.
`17. H. Stayskal and J. Herd. "Mutual
`Coupling Compensation in Small Array
`Antennas." IEEE Transactions. AP. Do
`camber 1990.
`
`Hans Stayslral chided electrical engineer-
`ing at the Royal Institute of Technology.
`Stockholm. Sweden. lrom whlch he received
`the degrees Clv. Ing. in 1963. Tekn. Llc.
`in
`1970 and Taltn. Dr. “1 1913. In 1962. he
`joined the Swedish Defense Research Insti-
`lute (FDA). where he worked on microwave
`radiation and scattering problems. In 1980.
`he gave up his position as chief section [or
`field and circuit theory and moved to the US.
`He now pursues his interests in elactromag
`notice and applied mathematics at the Rome
`Laboratory. Hansccm Air Force Base. MA.
`Dr. Steyskal is a fellow of the IEEE. I
`
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`REFERENCES
`1.
`P. Barton. "Digital Beamforming ior
`Radar." IEEE Proceedings. Vol. 127. Pt.
`F, August 4. 1930.
`2.
`H. Steyskal. “Digital Beamforming
`Antennas: An Introduction.“ Microwave
`Journal. January 1987.
`3.
`H. Stayskal and J. Floss. “Digital
`Beamlorrning lor Radar Systems." Mi-
`crowave Journal. January 1989.
`4.
`A. Farina. Antenna Based Signal
`Processing tor Radar Systems, Artech
`House. Norwood. MA. 1992.
`5.
`E. Barlle. Fl. Panto. T. Guella and J.
`Torres. ‘Perlormance oi Space-time
`Adaptive Airborne Radar." IEEE National
`Radar Conference. MA. USA. April 1993.
`6.
`Fl. Klemm. “Adaptive Air- and
`Space-borne M11 Under Jamming Con-
`ditions." IEEE National Radar Confer-
`ence. MA. USA. April 1993.
`7.
`J. Proakis and D. Manolakis. Digi-
`tal Signal Processing: Principles. Algo-
`The technology exists to make rea-
`rithms, and Applications, Macmillan
`sonably sized DBF arrays feasible
`Publishing Co.. New York. 1992, p. 419.
`8
`A.C.C. Wong. “Radar Digital
`today. For the near future. the high cost
`Beamlonning.“ Military Microwave Con-
`will necessitate strong economizing
`ference Proceedings. UK. 1982.
`with the number of digital channels.
`9. W. Gabriel. "Using Spectral Esti—
`For the more distant future. array an-
`mailon Techniques in Adaptive Prom-
`tenna systems that incorporate mixed
`lng Antenna Systems." IEEE Transac-
`tions. AP-34. March 1936.
`analog and digital circuitry are envi—
`10. E. Bruckner and J. Howell. “Adap-
`sioned. Reconfigurable, switched ana-
`live-Adaptive Array Processing." Pro-
`log subsystems will be used for their
`ceedings IEEE, Vol. 74. April 1986.
`tremendous bandwidth advantage. Dig-
`11.
`L. Eber. Digital Beam Steering An-
`
`
`Fig. 6 Correction of mutual coupling
`effects in an elght-elament array.
`
`CONCLUSION
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`.17
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`The Tom carts is new to the EW
`lei-cl Edi comers -n as new uh
`rm find people win more mms‘on
`oxpercnoe ‘Mlh monwave dares
`By trimming the technical tfiififis
`am taolmes oi the former Tl EiaCtrur:
`Techrciogy [Imam with vsmarr
`row leadersth. Tnion has created a
`'BWCElLil. remote new team
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`For cum scammed Stallions—
`usng TWTs. TWTAs. ldyslrms and
`negated suo~systems—
`talk to Triton.
`
`
`
`A hrroaary Approarh To l'rrhrrrra! Soirurmu
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`
`Solving EW Problems
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`JOURNAL of ELECTRONIC DEFENSE ' JULY '95
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`Page 6 of 6
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