Radar 2020: The Future of Radar SystemsWerner Wiesbeck, Leen Sit

Institut fur Hochfrequenztechnik und Elektronik (IHE)Karlsruhe Institute of Technology (KIT)

Karlsruhe, Germanywerner.wiesbeck@kit.edu

Abstract—The first radar was patented 110 years ago. Fastforward to today, radar applications have become ubiquitousin typical applications i.e. speed control, air traffic control,airborne and space-borne missions, military applications andremote sensing. Research for medical radar applications isalso progressing well for breast cancer detection and tumorlocalization. Automotive radar for safety and autonomous drivingare meanwhile being produced in millions per year. Despitethe significant technological advancements the radar systemtechnology unfortunately did not evolve like the communicationsand other related technologies for the last 20 years. With thedevelopment of high-speed electronic devices and higher demandfor radar systems, the current state-of-the-art radar systemconcepts will undergo a revolution. They will be conceptualizedand integrated in the current radar technologies leading torevolutionary radar systems. This will ultimately lead to newradar features and radar signal processing.

Keywords—Future Radar; MIMO Radar; DigitalBeamforming; Array Imaging

I. INTRODUCTION

The first radar was patented in 1904 by Christian Hulsmeyer[1]. It was a pulsed radar, radiating differentiated video pulses,generated by a spark gap. Hulsmeyer’s ideas were based on theexperiments by Heinrich Hertz in 1888, when Hertz detectedthe polarization dependent reflection of electromagnetic waves.Since then the radar system technology and signal processinghave significantly been improved for the state-of-the-art radarsat their time, for example, the 1938 Pulse Radar Patentof Colonel W. R. Blair. The first electronically scanningradar was the German Search Radar FuMG 41/42 Mammut-1in 1944. Numerous innovations in radar system technologyfollowed since then, e.g. the FMCW radar technology. Inthe same way the radar hardware technology and the radarsignal processing have advanced significantly. Until 1990the radar technology has always been a little ahead ofthe communications technology. But with the advent of thewide spread mobile communications, this situation changed.Although radars became equipped with new semiconductordevices and signal processing technologies, the system-levelradar concepts have remained the same since many years; theseradars still

• transmit the identical signal for their whole life• transmit only one frequency at a time (e.g. FMCW)• ’see’ only a small area at a time (e.g. Phased Array)• scan mechanically (e.g. airport radar)

Most of the current state-of-the-art radars, except for somemilitary radars, transmit an identical signal for the whole timeof their operation. Functionality-wise, this is inefficient sincethe radar will be limited to a narrow field of operation, whenthere are many different tasks/scenario that are encounteredeven for a single radar, e.g. near range-far range, tracking, lowrange resolution-high range resolution, etc. Regarding militaryradars, the radiation of uncorrelated signals is a necessityto avoid interception/detection, else their countermeasuresbecome straight forward.

The frequency spectrum became the most valuable resourcein the world since 20 years ago, because it is strictlylimited and is not transferable. As such it must be used asefficiently as possible. Technologies that exploit the spectrumfor opportunistic spectrum usage i.e. cognitive radio, ordual/combination systems i.e. radar-communication systems,are already being extensively researched to take full advantageof the limited spectrum.

Since the year 2000, the number of radars being usedis rapidly increasing. The fastest growing market for radarapplications is the automotive radar. Within a few yearsthere will be foreseeable millions of radars on the roads,with many cars equipped with up to five different radarssystems. Consequently there will be a selective inoperabilityin these radar systems due to strong inter-system interferences.Interference within the same frequency band can be avoidedif the radar signals are properly coded and are continuouslychanging for low cross-correlation, like in communications.

For scanning radars, the conventional method is still to usea narrow beam, scanning either mechanically or electronically(i.e. phased arrays). This approach of scanning a wide areafor target detection is highly inefficient. Mechanical scanningis cheap but slow; the phased array method is faster butexpensive. In both cases only one beamwidth area is scannedat a time.

The drawbacks of conventional radars mentioned aboveand some other deficiencies of the current state-of-the-artradars must be overcome in the next ten years. The potentialstrategies for future radar system concepts will include:

• intelligent signal coding, e.g. OFDM, CDMA• MIMO Radar - multiple transmit and receive antennas• digital beamforming for a higher angular resolution with

wide coverage without mechanical moving parts• array imaging - efficient systems of reduced size and cost• combination of radar-communication = RadCom978-1-4799-4195-7/14/$31.00 c©2014 IEEE

These new system technologies will cause a revolution inradar system concepts. In addition to the technical features,these will also allow the cost reduction of the systems, increasethe efficiency and the development of smart radars.

In the following sections these points will be explainedin more detail and summarized from the point of view ofcommunications and other well-known technologies.

II. RADAR SIGNAL CODING

A. Radar Signal Coding Requirements

The basic requirement for future radars is to cover timeand spectrum simultaneously, with each transmitted signaldifferently coded. This allows, as will be shown later, thecompression of the received signal in the dimensions oftime and frequency thus increasing the compression gainsignificantly up to 50 dB - 70 dB. This in turn allowsthe reduction of the transmit power due to the additionalcompression gain. For small radars e.g. automotive radars,this increases their power efficiency. For military applicationsthe detectability of these radar signals for localization andcountermeasures becomes much more difficult, because theyare similar to communications signals.

From communications several different coding schemes areknown e.g. CDMA (Code Division Multiple Access), DSSS(Direct Sequence Spread Spectrum), OFDM (OrthogonalFrequency Division Multiplexing) among others. For radarapplications the signal model selection must be madeaccording to (but not exclusively) [2], [3]:

• simplicity of signal generation• good decorrelation of simultaneous and consecutive

signals• ease of signal compression• simplicity of signal processing• possibility to transmit information• suitability for MIMO operation• simplicity of hardware realizationThis list is longer for special applications such as missile

control or ground penetrating radars. There is no one solutionfor all scenario; hence in this paper the OFDM coding isselected, because it covers several of the above arguments, likesimple realization, good de-correlation and simple processing.

B. OFDM Radar Signal Coding

The OFDM signal coding is well known fromcommunications. The available and/or required spectrumis covered by multiple orthogonal subcarriers, which are alldecorrelated due to their pulse duration T0 being inverse tothe subcarrier distance ∆f

∆f = 1/T0 (1)

In Fig. 1 the OFDM carrier arrangement is shown. Thedecorrelation results from the overlapping of the peak of aparticular subcarrier at the nulls of other subcarriers. A numberof OFDM carrier modulations such as QAM and PSK can beused. Arbitrary information such as music or data can then be

Fig. 1. Example of OFDM radar signal coding.

modulated onto the subcarriers. The spacing of the subcarriersis usually determined by the maximum expected Doppler shiftfD,max. By the rule of thumb the subcarrier spacing should bemore than 10 times the fD,max to mitigate the effect of inter-carrier interference during the radar processing. The number ofsubcarriers NC together with the subcarrier spacing ∆f resultin the available bandwidth B = NC∆f .

The total length of the transmit signal is composed of thenumber of carriers NC and the number of consecutive symbolsMsym in time, which together form the transmit pulse. Thetransmitted signal simultaneously covers the whole bandwidthover the duration of the transmit signal, MsymT0. In Fig. 2the transmitted ’block’, as a matrix, is shown.

Fig. 2. OFDM radar transmit matrix with NC carriers und Msym symbols.

The transmitted signal is a matrix D(m,n) with the timedomain representation in equation (2):

x(t) =

Msym−1∑m=0

NC−1∑n=0

DTx(mNC + n) exp(j2πn∆ft) ·

rect

(t−mT0

T0

), with mT0 ≤ t ≤ (m+ 1)T0.

(2)

The radar processing steps will be discussed in anothersection. It will be apparent then that the transmittedinformation influences the outcome of the radar processingif a direct correlation is used to extract the range and Dopplerinformation. This can be circumvented by using the proposedradar processing with only Fourier transformation in [4]. Ascan be seen from Fig. 2 , the total signal compression resultsfrom the compression in time domain multiplied by the onesin the frequency domain, which leads to the high compressiongain mentioned earlier.

III. DIGITAL BEAMFORMING

Radars illuminate an angular area defined by the horizontalbeamwidth ψ3dB and the vertical beamwidth θ3dB at a time.For operation over wider angular areas some sort of scanningeither mechanically or electronically (i.e. beam switching ora phased array switching) is required. Conventional analogmethods limit the effectiveness of scanning radars. A solutionto this is Digital Beamforming (DBF). The basic idea of DBFis to transmit/receive multiple independent weighted beamsformed by an array of antenna elements. The received multiplesignals by each receive antenna element are then downconverted for A/D conversion and stored in a memory. Fromthis memory these multiple beams can be digitally processedsimultaneously by a proper shift of phase and amplitudeweight wi conversion correlation. The major advantage isthat the signals are available for processing, not limitedby the pulse duration, and that the whole antenna elementbeam coverage can be simultaneously processed with multiplebeams. The angular resolution is however still determined bythe receive antenna beamwidth. Fig. 3 shows the principle ofthe received signal processing.

Fig. 3. Fig. 3. The principle of digital beamforming.

In the following the DBF technique is shown in more detailin Fig. 4. The single antenna elements receive the incoming

Fig. 4. Antenna element phase delay for a beam vector wave ψi.

wave with a phase φ resulting from their position in the arrayand the direction of the incoming wave ψi.

The angular distortion ∆φ = sin(ψi2πd/λ)is a function ofthe relative element spacing and the wave incident direction.The beam vector for a single impinging wave is:

~b(ψi) =[ej0∆ψ ej1∆ψ ej2∆ψ ... ej(N−1)∆ψ

](3)

The processing of the direction of the incoming wave is thensimple Fourier transformation, because the phases increaselinearly. For multiple beams a beam vector is set up for eachdirection and these are then combined to a beam matrix B, asshown in equation (4).

B =[~b(ψ1) ... ~b(ψi) ... ~b(ψl)

](4)

The DBF method can also be extended for a 2D scenarioas shown in Fig. 5.

Fig. 5. 2D digital Beamforming for a 2D antenna array with an incomingwave at ψi, θi.

For the 2D array to form the beam vector ~bi(θi, ψi) theelement phase shifts become:

∆φx = 2πdxλ

cos θi

∆φy = 2πdyλ

sinψi

(5)

The beam vector is then the Kronecker product of thesephase shifts. The processing again is a Fourier transformationin the two angular directions, where the multiple beams, inthe angular ranges covered by the single elements, can beprocessed simultaneously. This saves a significant amount oftime, especially the time spent for switching between beams.The most important aspect here is that the coverage of thewide area is simultaneous.

IV. MIMO RADAR

MIMO stands for Multiple-Input-Multiple-Output, atechnology that is coming up in communications in order toimprove the coverage, data rate and/or signal quality. For thefuture radar the same improvements are needed. MIMO radarssimultaneously radiate uncorrelated signals, for instance, indifferent directions, or in the same direction with orthogonalpolarization [4]–[7]. This improves the coverage and thereceived information quality. An example for the radiation ofthree simultaneous beams with a MIMO radar is shown inFig. 6. The decorrelation between the transmitted signals isrealized by OFDM spectral-interleaving [8]. In this case thetotal bandwidth for each transmit-receive channel is retainedhence there is no degradation in the radar range resolution.

Fig. 6. MIMO transmit array with three beams in the same direction.

The decorrelation of each transmit signal is important,otherwise small, remote targets might not show up on the radarimage. In practice a decorrelation of more than 70 dB can berealized with OFDM interleaved signals.

For near-range radars e.g. automotive radars, the couplingtransmit-receive should be less than -40 dB, because theseradars usually transmit while they receive the near rangesignals.

V. ARRAY IMAGING

While the knowledge and the significance of DBF andMIMO radar are already widespread, the radar communityis less aware of array imaging. This technique combines thefeatures of DBF with MIMO radar. The basic idea of arrayimaging is very simple: multiple transmit antennas radiate their

uncorrelated signals in the same area, the reflected multiplesignals are then received by each of the receive array antennas.For far-field operations the phase difference is assumed to beonly due to the different positions of the transmit antennassince the distance from the far-field target to each antennaelement is much larger than the antenna element spacing.This offsets the effect of the antenna elements’ real positionrelative to the object. Fig. 7a shows the real antennas and theradiation towards a far-field target. The received signals forthe two radiations have a phase difference, marked by the twocorresponding phase fronts. The phase front of Tx1 is delayeddue to its offset compared to Tx2. The lower phase front wouldalso result if two additional receive antennas are placed furtherleft (Fig. 7b). They appear as ’virtual receive antennas’ andtheir receive signals can be processed like real signals. Thereceive antennas are imaged at the transmit antenna and forma larger virtual array, at no additional cost or space.

In order to avoid redundant multiple copies of the samereceived signal with the same phase difference, the spacingdRx of the receive antennas and dTx of the transmit antennasare arranged in such a way in equation (6) to lead to the widestantenna basis.

dTx = NRxdRx (6)

The transmit antennas in this case usually have a spacing ofmore than a wave length. This results in grating lobes at thetransmit array radiation pattern. By spacing them according toequation (6), the nulls of the receive array will coincide withthe transmit grating lobes to eliminate them, see Fig. 8 for a3Tx by 3Rx array example.

Fig. 7. Array imaging with a MIMO radar for a simple 2Tx by 2Rx system;a) phase fronts for the two Tx-Rx arrays; b) imaging the phase front on thevirtual Rx antennas.

Fig. 8. Array factors for array imaging with a 3Tx by 3Rx array.

VI. RADAR 2020 SYSTEM BLOCK DIAGRAM

The integration of a MIMO radar with DBF operated withOFDM signals is shown in Fig. 9. The Radar 2020 system iscompletely digital except for the frontends. These frontendsare identical at the transmit and receive side respectively foreach channel. For higher frequencies and shorter ranges, e.g. inautomotive applications, they may be completely integrated inMMICs. OFDM MIMO signal generators are already availableon the market for certain applications. The OFDM parameterscan then be set according to the application requirements.

Fig. 9. Block diagram of the Radar 2020 with OFDM coding.

VII. RADAR SIGNAL PROCESSING

The processing strategy for future radar systems in thispaper is limited to OFDM. The transmit signal is given

by equation (2). The receive signal y(t) varies in complexamplitude A, range R and Doppler fD, see equation (7).

y(t) = A

Msym−1∑m=0

NC−1∑n=0

DTx(mNC+n) exp

(j2πn∆f

(t− 2R

c0

))·

exp (j2πfDt) rect

(t−mT0

T0

).

(7)

For the evaluation of the reflected signals the informationcontent in the OFDM receive signal is discarded via anelement-wise division of the received signal by the knowntransmit signal. What is left then are the amplitude, time shift(range) and frequency shift (Doppler). The resulting equation(8) in the frequency domain has a linear dependency withn and m, which corresponds to the subcarrier index in thefrequency axis and the symbol index in time axis respectively.

Y (m,n)=A

NC−1∑n=0

exp

(−j2πn∆f

2R

c0

)︸ ︷︷ ︸

Msym−1∑m=0

exp(j2πfDmT0)︸ ︷︷ ︸range Doppler

(8)

From the extracts of equation (8) the range and Doppler canbe determined by simple Fourier transformations (IFFT, FFT).In summary the angular, range and Doppler processing areall just Fourier transformations. Simulations and experimentshave proved that an arbitrary number of targets can beresolved using this technique [9], limited only by the physicalconstraints such as the bandwidth B and receive power PRx.The compression gain is the product of M×N . Super resolutionalgorithms like MUSIC can also be applied to generate anenhanced angular pseudo-spectrum. The overall efficiency ofthe Radar 2020 will in practice be around 6 dB to 10 dBhigher than for the current radars; and this can be investedin wider beams for simultaneous coverage of areas of interest,for example for airport radars.

VIII. RADCOM

The coding of the radar signal with OFDM or similarcommunication codes offers the possibility to includeinformation in the radar signal. With one transmission andone hardware equipment the systems can operate as radar andcommunication devices simultaneously. Applications can bethe communication of automotive radars with other cars orinfrastructure or military battlefield radars, see [10]–[13] .

IX. CONCLUSION

The new system technologies of the Radar 2020 will allowcomplete new functions and applications, which can replacemost of the existing system concepts [14]. The radars of thefuture will render more information, be more flexible andwill also be smaller and significantly cheaper. Best of allmost of these technologies for the future radar systems arealready available from other applications; they just have to

be just integrated in the future radars. The Radar 2020 willrevolutionize radar system engineering, and foreseeably, alsothe radar market.

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