A Novel Radar Receiver for Joint Radar And
Communication Systems
Sevda Şahin and Tolga Girici
Dept. of Electrical and Electronics Engineering
TOBB University of Economics and Technology
06560, Ankara, Turkey
{sevda.sahin}@etu.edu.tr, {tgirici}@etu.edu.tr
Abstract—Integration of radar and communication systems on
the same platform reveals the interference problems of these systems, as well as the installation problems on small scale platforms.
Joint radar and communication systems have significant potential
in solving these problems, as they reduce congestion both in the
spectrum and on the platform. In this article, the integration of
communication symbols into the radar signal is studied and a
new technique for radar receiver is proposed. The effects of the
integration methods on the performance of the radar receiver
are analyzed.
Index Terms—Chirp sequence, joint radar communication
(RadCom), integrated sensing and communication (ISAC), spectrum sharing, symbol error rate (SER), waveform design.
I. I NTRODUCTION
Recently, the frequency spectrum has intensified with the
increase in the variety of both military and civilian products in the field of wireless communication. The density in
the frequency spectrum prompts the companies that provide
communication networks to explore the possibility of using
frequency bands assigned to other usage concepts. In this
context, the radar band, which already has a wide spectrum,
stands out due to its high potential for common use. With the
widespread use of radar systems, which have both military
and civilian applications, modern radar systems have many
applications, especially for search/detection/diagnosis for air
traffic control, meteorology, defence, and security purposes.
While the 10 GHz and below radar bands are currently in
common use with systems such as 5G NR, LTE and Wi-Fi,
the common use of millimeter wave bands with radar systems
is on the agenda for 6G systems in the near future. Although
the common use of the frequency band seems like a suitable
solution to reduce the density in the frequency spectrum,
this use case brings up another problem such as interference
management. Various studies are carried out in both military
and civilian fields to solve the interference problem. In relation
to this, a diverse amount of research has been done within the
field of Communications and Radar Spectrum Sharing (CRSS).
Studies for CRSS are basically divided into two groups: (1)
Radar and Communication Coexistence (RCC), (2) Integrated
Sensing and Communication (ISAC). In the first method, RCC
requires an effective interference management so that the
radar and communication systems do not affect each other’s
performance and operation. In the second method, ISAC, it
is necessary to focus on a system solution that will support
both wireless communication and remote sensing. While there
is a need for data sharing or a central control system for
coordination between radar and communication systems in
RCC, the need for coordination and the density of the RF
spectrum are reduced by using the same RF signal for radar
and communication systems in the ISAC approach. There are
many recent studies on the ISAC method, especially in the
field of vehicle networks [1]. Sensing and communication
systems process information with different methods. Sensing
systems extract information from observations collected in a
noise environment. Communication systems focus on transmitting information via specially defined signals and extracting
information in the noise environment on the receiver side.
ISAC aims to combine these two functions and to achieve joint
performance by making trade-off analyses. ISAC can be used
not only in the field of cellular networks, but also in diverse
fields such as Wi-Fi networks, UAV networks, and military
communications [2]. In various studies, numerous waveforms
suitable for both sensing and communication functions are
examined to implement the ISAC concept. Joint waveforms are
studied in two main areas: sensing over communication signals
and communication over sensing signals. The waveform used
in both the concepts, changes randomly according to the
symbol sent by the transmitter. While this is an expected
situation for the communication receiver, it causes a result
that deteriorates the performance for the radar receiver. The
radar system works by integrating the reflections from the
target for a certain period of time while estimating the range
information regarding the target. Integration gain is obtained
due to the use of the same waveform throughout the integration
period, thus increasing the signal-to-noise ratio in the radar
receiver before the range estimation process. Target velocity
estimation is also made with the assumption that the signal
reflected from the target changes only at a negligible level
during this integration period. In ISAC application, since
the waveform changes randomly according to the transmitted
communication symbol during the integration process, this
affects both the range and speed estimation negatively. In this
paper, we used chirp pulse radar waveform to implement both
sensing and communication functions as defined in [3] and the
target and velocity estimation performance at the radar receiver
was analyzed according to the method proposed in [3]. As a
contribution, a new technique with better range and velocity
Fig. 1. Chirp signal for N pulses.
Fig. 2. Coded chirp signal for N pulses.
Fig. 3. Example of signature signals for M=4.
estimation performance is proposed. Performance analyses and
comparisons of both techniques in the case that the pulses
contain and do not contain the communication symbols were
made. In addition, the symbol error rate in the communication
receiver was also examined.
II. M ATHEMATICAL M ODELING
A. Chirped Radar Pulse
A chirp signal with pulse width τ , bandwidth B and initial
phase ϕ0 is expressed by (1) [3] .
2
Schirp (t) = ej(πµt
+2πf0 t+ϕ0 )
(1)
B. Communication Receiver
The signal received by the communication receiver is given
by (5). Here wk (t) represents Additive White Gaussian Noise
(AWGN).
yk (t) = SRadCom (t) + wk (t)
(5)
The demodulation of this signal at the receiver is usually
carried out using matched filtering. In this method, the crosscorrelation of the received signal with all possible signature
signals is calculated as given (6). Signature signals for 4
symbols are given in Fig. 3.
zi (t) = Corr(yk (t), Si (t)), i = 1, . . . , M
(6)
Here f0 is the carrier frequency and µ is the chirp rate. Also, t
is an element of the set [−τ /2, τ /2]. The chirp rate µ is given
in (2).
B
µ=
(2)
τ
Here, M is the number of symbols and Si (t) is the signature
signal of ith symbol. In cross-correlation, the signature signal
that gives the result with the highest peak value is accepted
as the sent symbol [4]. Estimation of the sent symbol, iest , is
determined by (7).
The frequency-time graph of the chirp signal for N pulses is
given in Fig. 1. As seen in Fig. 1, the initial frequency of the
chirp signal is constant for all pulses in a normal chirp radar
pulse. In order to encode the communication symbols within
the radar pulse, different initial frequencies are used for the
chirp signal for each symbol. As seen in Fig. 2 in the radarcommunication common waveform, each pulse is divided into
two and a chirp signal with a different initial frequency is used
for each segment. The mathematical expression of this signal
is given in (3).
iest = arg max (max {F (zi (t))}),
SRadCom (t) = Schirp (t − ∆tm )
(3)
∆tm is determined by (4).
∆tm
mτ
=
, m ∈ {1, 2, . . . , M − 1}
M
Here, M is the number of symbols.
(4)
i=1,...,M
f
(7)
F (.) represents the Fourier transform. The receiver find
the peak value of the FFT zi (t) for each i, than it find the
maximizing i.
C. Radar Receiver
The signal received by the radar receiver is given by (8).
Here A(.) represents amplitude of the reflected signal from the
target at range r0 [5].
gc (t) = A(r0 )SRadCom (t − td )
(8)
Assuming that the target speed is negligible compared to
the speed of light and the target range is far from the radar,
td can be written as (16).
td = 2r0 /c
(9)
If the target has constant speed v, the frequency of the
reflected signal received in the radar shifts by ±fD (Doppler
frequency). Doppler frequency is given in (10).
fD = wD /2π = f0 2v/c
(10)
Assuming that the radar signals travel at the speed of light,
the power of the signal reflected from the target in the radar
receiver is given by (11).
|Ar |2 = (2Pt Gt σ)/(ϵ0 c(4π)2 r4 )
(11)
where Pt , Gt , γ are the transmit power, antenna gain and the
radar cross section. In this case, the signal at the radar receiver
given in (5) can be updated as in (12) [5].
r
2Pt Gt σ jϕ0
2r0
1
e SRadCom t −
e−jωD t
gc (t) =
4πr02
ϵ0 c
c
(12)
Here, ϕ0 is the phase shifting because of the target reflection. Because ϕ0 has no effect on the range Doppler image,
in this study this shift is assumed as 0.
When the samples of the carrier-free signal SRadCom(t) sent
by the transmitter are expressed with the e vector, and the
samples of the carrier-free signal gc (t), which are received
by the receiver, are expressed with the r vector, information
about the target region can be extracted by performing the
correlation process of these two vectors (13). The correlation
process is repeated for the specified time intervals, and the
peaks of the correlation results are accepted as the target [5].
C = eT ⋆ r
(13)
Where eT can be express as given (14) for e = [e1 e2 e3 ]
eT = [e∗3 e∗2 e∗1 ]
(14)
When the length of the e is expressed as e and the length of
the r is expressed as r, the length of the C correlation string
is calculated as c + r − 1. The index with the peak of the
correlation array is used to calculate the delay time td of the
signal reflected from the target (15).
td = [tp − e]ts
(15)
where tp = arg max{gc (t)} is the time index of the peak
received sample.
The target range r0 corresponding to this delay time is
calculated as given in (16).
r0 = ctd /2
(16)
The radar system generates the range Doppler plot by emitting N coherent pulses and calculating the correlation of each
of these pulses with its own reflected pulse. The time it takes
to send and receive N pulses is called the coherent processing
interval (CPI). The result of the correlation operation of the
first pulse with its own reflected pulse forms the first row
of a matrix. The rows of the matrix are filled by repeating
this process for N pulses. The frequency spectrum of each
column of the matrix is found by discrete Fourier Transform
(DFT) operation. The frequency spectrum for each column is
calculated as given in 17 [5].


1


ejωD T


 × (Ck )
 ejωD 2T
(17)




...
ejωD (N −1)T
Where Ck is a constant changes from column to column
but, being constant in time, it’s not detected by the DFT
and so does not affect the spectrum produced. Hence The
corresponding angular velocity is calculated by multiplying
−c
the frequency in each column by 2f
.
0
D. Phase Correction Method For ISAC Radar Receiver
To enhance receiver performance, we used phase correction
method proposed in [3]. In this method, each pulse in the IF
band is multiplied by a phase correction factor corresponding
to the symbol carried by the pulse as given in (18). Radar
signal processing is performed after the phase correction.
Scorr (n) = F −1 F [SIF (n)].e−j∆Ωm ∆tm
(18)
Here ∆Ωm represents phase correction factor and it is
defined for each symbol.
E. New Technique For ISAC Radar Receiver
In this new technique, instead of passing each pulse on the
radar receiver through the same match filter as in the classical
method, the radar pulses received at the receiver are passed
through a match filter which is compatible with the communication signal sent by the transmitter. To achieve this, matched
filters are used in the radar receiver as many as the number
of symbols that can be sent from the transmitter. Matched
filters can be designed by using (19) for each communication
symbols.
M F (i) = e2jπ(
0.5B
τ
)( t(i)
fs )
2
(19)
Here, fs is the sampling rate and t(i) can be calculated by
using (20).
t(i) = mod[K − k(i) − 1 + ti , K]
(20)
Where ti is time index matrix and K and k(i) are given by
(21) and (22) respectively.
K = τ fs
(21)
k(i) = Km(i)/M
(22)
This new technique is named as matched filter bank technique in this paper.
Fig. 4. Range Doppler Characteristics without communication symbols,
f0 =10GHz.
Simulation Parameters
Values
Radar Carrier Frequency
10 GHz
Radar Range
75km
Radar Blind Range
30km
Radar Range Resolution
731.7m
Radar False Alarm Probability
10−6
Radar Target Range
36444m
Radar Target Speed
4m/s
Number of Communication Symbols
4
TABLE I
S IMULATION PARAMETERS
III. S IMULATIONS
In this study, the coding of the communication symbols
of the chirp pulse radar signal was studied. As a result
of the coding of the communication signals, the detection
performance of the radar was examined, and the method
proposed in [3] was used to improve the radar performance.
One of symbols given in Fig. 3 was used randomly in each
of the pulses produced for the radar signal. Radar detection
performances in the radar receiver when the pulses contain
and do not contain the communication symbols are examined
to analyze the amount of distortion due to coding for M =
4. Then, the analyses were repeated using the new technique
proposed in the Section II-E and the performance of the new
technique was evaluated.
Fig. 5. Range Doppler characteristics with communication symbols for
conventional radar receiver, f0 =10GHz, M=4.
B. Radar Receiver Performance With Communication Symbols and Conventional Receiver
The radar receiver performance when the pulses contain
communication symbols is determined by using conventional
receiver for chirp signal. The range Doppler image is given in
Fig. 5.
As seen in Fig. 5, because we use conventional receiver for
chirp signal the receiver detected multiple targets.
C. Phase Corrected Radar Receiver Performance With Communication Symbols
To enhance receiver performance, we used phase correction
method proposed in [3]. In this method, each pulse in the IF
band is multiplied by a phase correction factor corresponding
to the symbol carried by the pulse as defined in Section
II-D. Radar signal processing is performed after the phase
correction. The range Doppler image is given in Fig. 6.
As seen in Fig. 6, the receiver performance was improved
and false targets are eliminated by this method, but no significant improvement was observed in the speed detection
performance. On the other hand, as the carrier frequency
increases, the accuracy of the phase correction coefficient
becomes more effective on the performance of the radar
receiver.
D. New Technique for ISAC Radar Receiver
A. Radar Receiver Performance Without Communication Symbols
The radar receiver performance when the pulses do not
contain communication symbols is determined by using conventional receiver for chirp signal. The range Doppler image
is given in Fig. 4. Parameters used in the simulation are given
in Table I.
As seen in Fig. 4, in this scenario the conventional receiver
detected single target with high range accuracy and acceptable
speed accuracy.
To improve speed accuracy and enhance receiver performance, instead of passing each pulse on the radar receiver
through the same match filter as in the classical method, the
radar pulses received at the receiver are passed through a
match filter which is selected from a matched filter bank as
defined in Section II-E. The range Doppler image is given in
Fig. 7.
As seen in Fig. 7, the speed accuracy of the receiver was
significantly improved by this method. In this phase of the
study, following the successful results of the matched filter
Fig. 6. Range Doppler characteristics with communication symbols for phase
corrected radar receiver, f0 =10GHz, M=4.
Fig. 7. Range Doppler characteristics with communication symbols for
matched filter bank radar receiver, f0 =10GHz, M=14.
bank method in these low-frequency, M = symbols analyses,
additional simulations were carried out using the parameters
given in the Table II to evaluate the performance analyses for
high-frequency, high-range resolution radar signals for various
number of symbols.
Simulation Parameters
Values
Radar Carrier Frequency
85 GHz
Radar Range
4.5km
Radar Blind Range
500m
Radar Range Resolution
2m
Radar False Alarm Probability
10−6
Radar Target Range
3026m
Radar Target Speed
25m/s
Number of Communication Symbols 2, 4, 8, 16
TABLE II
S IMULATION PARAMETERS FOR H IGH F REQUENCY
Range Doppler characteristics of phase corrected and
Fig. 8. Range Doppler characteristics with communication symbols for phase
corrected radar receiver, f0 =10GHz, M=16.
Fig. 9. Range Doppler characteristics with communication symbols for
matched filter bank radar receiver, f0 =10GHz, M=16.
matched filter bank techniques are given in Fig. 8, Fig. 9 and
Fig. 10 for M = 16.
As seen in Fig. 8, Fig. 9 and Fig. 10, the increase in
the number of symbols in both low frequency and high
frequency does not cause a significant change in the receiver’s
range Doppler characteristic for phase corrected and matched
filter bank techniques. In order to analyze the performance
of the radar receiver of the symbol number used in the
communication channel in more detail, the range and speed
estimation of the target detected in the radar receiver was made
for various symbol numbers. estimation error was calculated
according to the mean square error method. As can be seen
in the Fig. 11 and 12, using the proposed new method, range
and speed estimation is made with high accuracy regardless
of the number of symbols on the radar receiver.
Fig. 10. Range Doppler characteristics with communication symbols for
matched filter bank radar receiver, f0 =85GHz, M=16.
Fig. 11. Mean Square range error vs. number of communications bits per
symbol. Radar performance is not affected by the number of communication
bits. The proposed matched filter based method results in negligible range
error. Performance is better at higher carrier frequency.
E. Communication Receiver Performance
Parameters given in the Table I. is used to analyze the communication receiver performance. The symbol error rate (SER)
is calculated according to procedure defined in Section II-B by
using 30000 pulses. SER performance of the communication
receiver is given in Fig. 13.
IV. C ONCLUSIONS
In this article, the performance loss in the radar receiver is
analyzed when the conventional pulsed chirp waveform is used
for the communication function. The proposed matched filter
bank method was used to compensate for this performance
loss. With this method, range and velocity estimation errors
caused by the symbols used in the communication channel on
the radar receiver are eliminated and a high-accuracy range and
Fig. 12. Mean Square speed error vs. number of communications bits per
symbol. The proposed matched filter based method results in negligible speed
error. Performance is better at lower carrier frequency with low speed.
Fig. 13. Symbol Error Rate in the communication receiver for M=4.
speed estimation is made on the radar receiver, independent
of the number of symbols used.
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