Code shift keying based joint radar and communications for EMCON applications

Digital Signal Processing 80 (2018) 48–56

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Digital Signal Processing www.elsevier.com/locate/dsp

Code shift keying based joint radar and communications for EMCON applications Thomas W. Tedesso a,∗ , Ric Romero b a b

Department of Electrical and Computer Engineering, United States Naval Academy, Annapolis, MD, United States of America Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA, United States of America

a r t i c l e

i n f o

Article history: Available online 28 May 2018 Keywords: Radar embedded communications Digital communications Signal processing Estimation

a b s t r a c t Due to the explosion in the demand for broadband wireless services by consumers, wireless network service providers require increased frequency allocations from an already crowded frequency spectrum. In an effort to satisfy the increased frequency spectrum requirements of wireless communications networks, several methods have been proposed to allow communication systems and radars to co-exist within the same bandwidth or adjacent frequency bands while minimizing or preventing mutual interference. Most methods explored in the literature focus on the use of cognitive sensing and dynamic spectrum allocation. Other proposed methods to prevent mutual interference between radar and communications systems focus on waveform design. In this manuscript, a dual function communication and radar system with EMCON applications is investigated that uses Gold or Kasami codes in a code shift keying digital modulation scheme. The use of both binary phase shift keying (BPSK) and quaternary phase shift keying (QPSK) to modulate the code bits is investigated. The communications signal is used as the radar signal to implement a pseudo-random BPSK or QPSK coded radar. The symbol error rate (SER) of the communication system is determined through Monte Carlo simulations and compared to an SER upper bound for M-ary frequency shift keying. The radar signal’s periodic autocorrelation function (PACF) and periodic ambiguity function are also examined demonstrating the schemes potential for use in a low probability of intercept radar application. The radar signal’s characteristics are compared when using pseudo-random BPSK and QPSK modulations. Published by Elsevier Inc.

1. Introduction The proliferation of commercial mobile devices and consumer demand for streaming video and music applications have increased bandwidth requirements of mobile wireless communication networks. Frequency spectrum allocations for military and commercial radar systems such as air traffic control radars are normally segregated from other users to avoid interfering with these critical systems. However, the demand for increased bandwidth allocations by mobile network providers spurred innovation in developing systems and protocols that allow the coexistence of radar and communication systems within the same bandwidth while preventing or minimizing mutual interference. To satisfy the demand for increased frequency spectrum resources, various approaches that employed cognitive radar and radio systems and dynamic spectrum allocation schemes were proposed [1]. Other approaches used

*

Corresponding author. E-mail addresses: [email protected] (T.W. Tedesso), [email protected] (R. Romero). https://doi.org/10.1016/j.dsp.2018.05.013 1051-2004/Published by Elsevier Inc.

waveform design and frequency spectrum shaping techniques to allow radar and communications signals to coexistence without causing mutual interference. Geographic exclusion zones (GEZ), dynamic frequency selection, and temporal sharing are currently used to prevent mutual interference of radar and communication systems [2]. These methods have inefficiencies that limit their effectiveness. Cognitive sensing was proposed as a means of sensing and dynamically allocating the frequency spectrum resources to prevent interference between the radar and cellular communication systems while allowing more efficient use of spectrum resources. A database assisted spatiotemporal deconfliction framework based on a measurement study of a weather radar with a quasi-periodic scan rate is presented in [2]. This framework incorporates use of (a) a GEZ around the primary user (radar system) where the secondary user (communication system) always interferes with the radar user and transmission is not allowed, (b) a geographic free transmission area (FTA) where the secondary user can transmit at anytime without interfering with the primary user, and (c) a temporal sharing zone (TSZ) between the GEZ and the FTA, where the secondary user avoids transmitting when the radar’s main beam is pointed at the secondary

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user. A radar database signals the users when the radar scan rate changes, etc., in the temporal sharing protocol. A related protocol is presented in [3] which uses a radio environment map architecture to permit shared access (SA) to Internet of things (IoT) users in frequency channels allocated for radar systems as primary users. Another approach to prevent mutual interference between radar and cellular communication systems adopts a spatiotemporal analytical approach to adaptive base station power control [4]. The wireless communication system and radar system operate in adjacent channels, and the cellular base station knows the radar system’s characteristics. The base station varies its transmit power depending on whether it is in the main lobe or side lobes of the radar antenna to prevent interfering with the radar. Both analytical and simulation results are presented, demonstrating the feasibility of this approach. In [5], a WiFi protocol that detects radar signals during WiFi listening periods is examined. If a radar signal is present, the WiFi system switches to a clear channel to avoid interfering with the radar. The performance of a radar detection scheme relying on WiFi idle/quiet periods is characterized and trade-offs between network throughput and improved detection performance are illustrated. Other means of minimizing interference between radar and communications systems rely on spatial signal processing. An example of using spatial signal processing is presented in [6]. The interference of cellular communication system base stations on a coherent multiple-input multiple-output (MIMO) radar is minimized by inserting nulls in the radar’s receive antenna beam pattern towards the interfering transmitters. Another method employing spatial signal processing is presented in [7]. In this case, null space projections are used to attenuate the power transmitted by a shipboard MIMO radar in the direction of cellular network base stations. Through the use of null space projections, the radar system minimizes interference with the communication system at the expense of target detection in the direction of the base stations. In [8], a technique that employs side lobe control of the transmit beam forming in tandem with waveform diversity enables communication using the same pulse radar spectrum. Multiple orthogonal waveforms are used to embed a sequence of information bits. The side lobe levels towards the communication receiver are controlled to have two distinct levels by designing two different beam forming weighting vectors. The receiver interprets the bit associated with a certain waveform as 0 or 1 based upon which weighting vector was used. Other methods that explore dual function MIMO radar-communication systems are presented in [9–11]. A method of embedding communication information into a radar signal is presented in [9]. A sequence of Q bits is mapped into a dictionary of 2 Q phase rotations. A pair of transmit orthogonal waveforms is used with 2 Q pairs of transmit beam forming weight vectors to embed an entry from the phase rotation dictionary into each radar pulse. In [10], a set of orthogonal waveforms using frequency hopping (FH) codes are used to implement the primary function MIMO radar. The secondary communication function is implemented through embedding one PSK communication symbol in each frequency hop. Another method of embedding communications into a MIMO radar is presented in [11], where the communication symbols are embedded into the radar signal by shuffling independent waveforms across the transmit antennas. Waveform design has been explored as another method to minimize interference between coexisting radar and communication signals. Spectral shaping of a pulsed radar’s waveform using a water-filling technique to minimize interference with legacy quaternary phase-shift keying (QPSK) modulated communication systems is explored in [12]. Monte Carlo simulations demonstrate that the probability of target detection performance in the presence of

49

communication system interference is improved when using the shaped radar waveform compared to using a traditional wideband pulsed radar waveform. When in the presence of radar interference using the shaped radar waveform, the legacy QPSK communication system’s symbol error rate (SER) approximated the theoretical SER of QPSK in a channel corrupted by additive white Gaussian noise (AWGN). Another example of waveform design embeds an orthogonal frequency division multiplexing (OFDM) signal within a spectrally notched ultra-wideband (UWB) random noise radar waveform [13]. The simulation results presented in [13] demonstrate that a reliable multi-user communications platform exists and that the radar range and Doppler resolution remain consistent with those of a random noise radar provided the fragmented gap is less than 30-percent of the bandwidth. A low probability of intercept (LPI) communication strategy is presented in [14–18] where the communication symbols are embedded in the backscatter of a high power pulsed radar system on an intra-pulse basis. This concept is expanded upon in [19] where three separate LPI communication symbol design strategies are presented: dominant projection, shaped dominant projection, and shaped water filling. These strategies are compared to the performance when using direct sequence spread spectrum (DSSS) spreading vectors as the communication symbol alphabet. The probability of symbol detection is examined for both the intended receiver as well as a clairvoyant intercept receiver. In [20], a conceptual covert communication system was analyzed which embedded a differential phase shift keying (DPSK) digital communication signal into radar backscatter. The radar signal parameters were estimated and subtracted from the received signal allowing detection of the embedded signal. Monte Carlo simulation results are presented to demonstrate the performance of the concept. Another method of embedding a continuous phase modulated (CPM) communication signal onto a polyphase-coded frequency-modulated (PCFM) radar signal was proposed and the trade-off between radar performance and communication system bit-rate was examined in [21]. In [22], filtering methods are examined to address the range side lobe modulation issues discussed in [21]. A dual function radar and communication system is proposed in this manuscript that employs code shift keying (CSK) using Gold or Kasami codes as the communication symbols and the resulting pseudo-random binary phase coded communication signal as continuous wave radar waveform. A potential application of such a system would be during naval task force operations in a restricted electromagnetic emissions control (EMCON) environment. Maritime operations use EMCON to conceal fleet units from detection by adversary passive direction finding systems [23]. The use of EMCON during fleet operations and the development of LPI sensors are expanding as the concept of Electromagnetic Maneuver Warfare (EMW) is implemented in U.S. Navy operations [24]. The proposed dual function radar and communication system would allow a naval task force to operate an LPI radar system while relaying track data to friendly units without the requirements of establishing a separate dedicated communications link that may expose platforms to passive detection by adversaries. The communication system’s performance is evaluated via Monte Carlo simulations for both Gold codes and Kasami codes of various code lengths. The SERs are compared to an upper bound of M-ary frequency shift keying (MFSK)/MCSK using an orthogonal code library. The characteristics of the radar waveform are presented for examples of Gold and Kasami coded sequences by examining periodic autocorrelation function (PACF) and periodic ambiguity function (PAF) of the radar waveforms. The maximum range side lobe level, the range resolution, maximum range, maximum Doppler frequency, and data rate are presented for different code types and lengths. In addition to examining the above de-

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Fig. 1. (a) Block diagram of dual function code shift keying communications and a pseudo-random binary phase coded radar transmitter. (b) Block diagram of code shift keying receiver.

scribed modulation using binary phase shift keying for each chip of the CSK symbol, the use of QPSK to modulate each chip of two separate symbols as in-phase and quadrature components is examined. As a result, the radar signal becomes a pseudo-random QPSK coded signal. The pseudo-random QPSK coded radar signal’s characteristics are examined through presenting the PACF and the zero delay cut of the PAF. The pseudo-random QPSK radar signal’s performance is compared to that of the pseudo-random BPSK radar signal. The primary contribution of this paper is the examination of using Gold or Kasami codes in a dual function CSK communication and pseudo-random binary phase coded radar system with applications in naval EMCON scenarios. Performance curves for the MCSK communications system when using Gold and Kasami codes are developed through performing Monte Carlo simulations. These SER curves are presented and compared to an upper theoretical bound for MFSK/MCSK. Also, the resulting pseudo-random binary phase coded radar’s waveform is characterized by presenting the zero delay and zero Doppler cuts of the periodic ambiguity function. Additionally, we examine using QPSK modulation to transmit the bits of the Gold or Kasami coded symbols which results in a pseudo-random QPSK radar system. The pseudo-random QPSK radar’s waveform characteristics are presented and are compared to those of a pseudo-random BPSK radar system. When using either BPSK or QPSK coding, the radar and communication signals are the same waveforms; therefore, both communication and radar system operation occur without the mutual interference problems normally associated with using two different waveforms. The remainder of this manuscript is organized as follows: in section 2, the dual function radar and communication system is presented and the analysis and simulation methods used are discussed. In section 3, the Monte Carlo simulation results and radar waveform PAF and PACF are presented. The results of the Monte Carlo simulations of the communication receiver are compared to those of M-ary frequency shift keying (MFSK). The radar PAF and PACF are compared to the results of a random binary phase coded radar system that was presented in [25,26] and discussed in [27]. Additionally, the PACF and the zero delay cut of the PAF of a pseudo-random QPSK coded radar signal is examined for both Gold and Kasami codes. The waveform characteristics for the pseudo-random QPSK coded radar signal are compared to that of the pseudo-random BPSK coded radar signal. In section 4, conclusions are made and avenues to further explore this concept are discussed.

2. Methods Pseudo-random sequences such as Gold codes and Kasami codes are used as scrambling sequences in wideband code division multiple access (WCDMA) technology [28]. Gold codes and Kasami codes are generated from preferred pairs of maximal length binary sequences (m-sequences) and have good cross-correlation properties [29]. The cross correlation of two Gold codes takes on one of three values, {−t (k), −1, t (k) − 2} [28–30], where



t (n) =

1+2 1+2

k +1 2

,

for k odd

k +2 2

,

for k even,

(1)

and k is the degree of the generator polynomials. The cross correlation between Kasami codes also take on distinct values. For the small set of Kasami codes, the cross correlation takes on values from the set of {−1, −(2k/2 + 1), 2k/2 − 1}. For the large set of Kasami codes, the cross correlation takes on one of five values {−1, −1 ± 2k/2 , −1 ± 2(k+1)/2 } [28,29]. The crosscorrelation of the small set of Kasami codes are optimal with respect to the Welch lower bound [29,31]. The Welch lower bound is the lower bound on the cross-correlation between any pair of binary sequences with period N in a set of M sequences,



R c (k) ≥ N

M −1 MN − 1

(2)

where R c is the cross-correlation function, the code length is N = 2k − 1, and k is the degree of the generator polynomials. Due to their good cross-correlation properties, Gold and Kasami codes were chosen to be evaluated as the communication symbol sets in a dual function communication and radar system using CSK modulation. Since Gold and Kasami codes are a pseudo-random binary sequences, their use as communications symbols allows for the communication signal to be used in a pseudo-random binary phase coded noise radar application. Based upon this premise, a dual function communications and radar system is proposed which uses the same signal for both functions negating the mutual interference problems discussed earlier. A simplified block diagram of the radar transmitter and receiver are displayed in Fig. 1 which uses BPSK to modulate the bits of the communication symbol. The radar transmits the CSK communication signal in an omni-directional manner to allow 360◦ transmission of communication signal. The radar receiver antenna requires a narrow beam width to achieve sufficient angular resolution needed for the target scenario. The receive antenna would

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scan the horizon via a mechanically rotated antenna or via electronic steering if a phased array radar is employed. The particular radar antenna design and steering mechanism are beyond the scope of this paper and are not addressed in this manuscript. A random binary phase coded radar (RBPCR) is presented in [25–27]. The estimated range resolution of a RBPCR is

R =

ctb 2

(3)

,

where tb is the code’s bit period and c is the speed of light. To determine the targets range, the receiver correlates the return signal with delayed versions of the transmitted signal. The maximum range of the RBPCR is

R max =

cT c 2

=

cN c tb 2

,

1 2N c tb

(5)

.

From (4), R max is directly proportional to the N c . However, νmax is inversely proportional to the N c in (5). Therefore, a trade-off between achieving a large R max and a large νmax is required. To allow increasing R max while not impacting νmax , the length of the correlator used for range detection can be increased to represent multiple communication symbols. If L symbols are used,

R max =

cLN c tb 2

(6)

.

A simplified block diagram of the CSK communication receiver is displayed in Fig. 1(b). The signal is down converted to baseband and passed through a bank of matched filters which correspond to the code of each symbol. Maximum likelihood detection is performed by choosing the matched filter with the maximum output. This method is similar to one of the demodulation methods for using large set Kasami codes in M-CSK ultra-wideband communications that was presented in [32]. Monte Carlo simulations were performed to evaluate the communication receiver’s SER. In the Monte Carlo simulations, coherent detection is assumed as well as transmitter and receiver synchronization. The results of the Monte Carlo simulations are presented in the following section. The radar waveform characteristics are evaluated by examining the periodic autocorrelation function (PACF),

R xx =

Nc 1 

Nc

s[n]s∗ [n − r ],

(7)

n =0

where s[n] is the signal’s complex envelope normalized in time, and the periodic ambiguity function (PAF),

  N c tb     1  ∗ j2 π ν t )  |χ (τ , ν )| =  s (t ) s (t + τ ) e ( dt  ,  N c tb 

quadrature channels entering two separate matched filter banks. The implementation of the radar receiver would be the same for both BPSK and QPSK phase encoding. 3. Results and discussion To determine the SER of the communications system using Gold codes and Kasami codes, Monte Carlo simulations were conducted using 1 × 107 trials for several different code lengths. The simulation results were compared to the theoretical upper bound for SER of MFSK/MCSK [34],

 P E ( M ) ≤ ( M − 1) Q

(8)

0

where τ is the delay, and ν is the Doppler shift. The MATLAB programs in [33] and the MATLAB phased-array toolbox are used to generate the plots of the PACF, PAF and zero delay cut of the PAF. For the case where QPSK modulation is examined, the phase encoder in the transmitter in Fig. 1(a) is modified to replace the binary phase encoder with a quaternary phase-shift keying encoder. The symbols are multiplexed so that in-phase channel modulates the symbol’s odd bits and the quadrature channel modulates the symbol’s even bits. Similarly, for the communications receiver in Fig. 1(b), QPSK demodulation would occur with the in-phase and

Es



N0

(4)

where T c is the code period and N c is the number of bits per code. The maximum Doppler frequency is

νmax =

51

,

(9)

where E s / N 0 is the symbol energy to noise energy ratio, M = 2k is the number of symbols in the modulation scheme, and the Q function is defined as

Q (x) = √

1

(2π )

∞

exp −

x2 2

 .

(10)

x

In Fig. 2(a), the SER is plotted versus E s / N 0 when using Gold codes as the communication symbols for codes of different lengths. The SER curves are compared to the upper bound defined in (9). From the results in Fig. 2(a), the SER when using Gold code symbols mirrored the upper bound for MFSK. Similarly, the SER for the communication system when using Kasami codes as the communication symbols is displayed in Fig. 2(b). Both small set and large set Kasami codes were examined. In Fig. 2(b), the SERs are displayed when using the small set of Kasami codes for M = 16 and M = 64. For these cases, the SER is less than the upper bound defined in (9) due to the code length being greater than the number of codes. The results when using large set Kasami codes are also displayed in Fig. 2(b). Large set Kasami codes allowed for M = 21.5k symbols for code lengths, N c = 2k − 1. The results for a ( N c , M ) = (63, 512) large set Kasami code are also shown in Fig. 2(b). The results for the SER closely match the upper bound of (9) at high values of E s / N 0 . For the case where QPSK modulation was performed, the SER results are the same as those presented in Fig. 2(a) and Fig. 2(b) since the BER of QPSK and BPSK are equal for the same E b / N 0 . In this case, the values of E s / N 0 for the in-phase and quadrature channel of the QPSK modulator are equal. The PACF, the zero delay cut of the PAF, and the PAF for radar system using a 127-bit Gold code and 255-bit Kasami code are displayed in Fig. 3 and Fig. 4 respectively. The plots were generated using a sampling frequency, f s = 1 GHz, a carrier frequency of f c = 100 MHz, and a bit time, tb = 10 ns. The maximum side lobe level of PACF for the 127-bit Gold code is −17.5 dB. The PACF side lobe level for the 255-bit small set Kasami code is −23.5 dB. The plots of the PACF and zero delay cut of the PAF are shown in Figs. 3(a), 3(b), 4(a), and 4(b). The Doppler resolution for the codes is dependent upon code length, bit length, and the carrier frequency. For the plots examined, square pulses were used as the complex envelope of the waveform. The side lobe levels for the PACF are comparable to those reported in [25,27]. In Fig. 5, the PACF and zero delay cut are shown when using two different 127 bit Gold code symbols as the radar signal. The results demonstrate a reduction in range side lobe levels as a result of the longer code length which would be expected. For the case of a pseudo-random QPSK radar, the waveform characteristics when using a 127-bit code and a 255-bit small set Kasami code are examined. The PACF and zero delay cut of the PAF when using 127-bit Gold codes are displayed in Fig. 6. The PACF and zero delay cut of the PAF when using 255-bit Kasami codes

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Fig. 2. (a) Symbol error rate for code shift keying using Gold codes. The (o) markers indicate Gold codes and (x) markers are MFSK modulation. The solid line (−) indicates M = 32, dashed line (−−) indicates M = 64, dashed-dot line (− · −) indicates M = 128, and the dotted line (· · · ) indicates M = 512. (b) Symbol error rate for code shift keying using Kasami codes. The (o) markers indicate Kasami codes and (x) markers are MFSK modulation. The solid line (−) indicates M = 16, dashed line (−−) indicates M = 64, and the dotted line (· · · ) indicates M = 512. For M = {16, 64}, small set Kasami codes were used. For M = 512, the large set Kasami codes were used.

Fig. 3. (a) Periodic autocorrelation function (zero Doppler cut) for 127-bit Gold code. (b) Zero delay cut of periodic ambiguity function for 127-bit Gold code. (c) Example of periodic ambiguity function for 127-bit Gold code symbol.

are displayed in Fig. 7. In both cases, the PACFs are similar to those seen when using BPSK; however, unlike the PACFs which used BPSK modulation, the PACFs when using QPSK modulation exhibit variations from the relatively flat profile seen outside of the peak

value when using BPSK modulation. The pseudo-random QPSK radar maintains good range resolution when using Gold codes as seen in Fig. 6 and Kasami codes, shown in Fig. 7. In each case, the peak range side lobe levels were within 3 dB of those seen using

T.W. Tedesso, R. Romero / Digital Signal Processing 80 (2018) 48–56

53

Fig. 4. (a) Periodic autocorrelation function (zero Doppler cut) for 255-bit Kasami code. (b) Zero delay cut for 255-bit Kasami code. (c) Example of periodic ambiguity function for a 255-bit small set Kasami code.

Fig. 5. (a) Periodic autocorrelation function (zero Doppler cut) for two symbols of a 127-bit Gold code. (b) Zero delay cut of periodic ambiguity function for two symbols of a 127-bit Gold code.

Fig. 6. QPSK signaling using 127-bit Gold codes in the inphase and quadrature channels. (a) Periodic autocorrelation function (zero Doppler cut). (b) Zero delay cut.

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Fig. 7. QPSK signaling using 255-bit small set Kasami codes in the in-phase and quadrature channels. (a) Periodic autocorrelation function (zero Doppler cut). (b) Zero delay cut.

Fig. 8. (a) Zero Doppler cut for 255-bit small set Kasami code for pseudo-random BPSK coded radar. (b) Zero Doppler cut for 255-bit small set Kasami codes for pseudorandom QPSK coded radar. (c) Zero delay cut for 255-bit small set Kasami code for pseudo-random BPSK coded radar. (d) Zero delay cut for 255-bit small set Kasami codes for pseudo-random QPSK coded radar.

the same length codes for the pseudo-random binary phase coded radar in Fig. 3 and Fig. 4. In the previous figures displaying the zero delay cut of the PAF and PACF for the Gold and Kasami coded waveforms, magnified versions were displayed so the range and frequency resolution could be seen. When comparing the pseudorandom BPSK and QPSK coded radar waveforms, they both have approximately equal range and Doppler resolution which would be expected. However, comparing the results in Fig. 8(a) to Fig. 8(b), variation in the PACF of the QPSK coded signal is seen compared to PACF of the BPSK coded signal. When examining the zero delay cut of the PAF across the entire frequency range for a 255-bit small set Kasami code using BPSK and QPSK as shown in Fig. 8(c) and Fig. 8(d) respectively, there are relatively high side lobes when QPSK coding is used compared to when using BPSK coding. This characteristic was also noted in the Gold coded signals using QPSK. Examples of the radar parameters when using different codes is presented in Table 1 when tb = 10 ns. Based on the data presented in Table 1, there is a trade off between the various radar parameters  R, R max , and νmax . The value of tb determines range resolution, while R max and νmax are determined by the code period N c tb . The data rate depends upon the effective code rate, M / N c . To increase R max a longer code could be used, or the detector could correlate on multiple symbols at the expense of reduced νmax . If we choose to correlate on ten symbols, our radar parameters would change to those listed in Table 2. Alternately, we could

Table 1 Example of pseudo-random binary phase coded radar parameters when using one symbol for correlation. Code (Nc , M )

R

R max (m)

νmax

(m)

(kHz)

Data rate (Mb/s)

Gold (127, 128) Gold (511, 512) Kasami (255, 64) Kasami (63, 512)

1.5 1.5 1.5 1.5

190.5 766.5 382.5 94.2

393.7 97.8 196.1 793.6

5.51 1.76 2.35 14.28

Table 2 Example of pseudo-random binary phase coded radar parameters when using ten symbol for correlation. Code (Nc , M )

R

R max (m)

νmax

(m)

(kHz)

Data rate (Mb/s)

Gold (127, 128) Gold (511, 512) Kasami (255, 64) Kasami (63, 512)

1.5 1.5 1.5 1.5

1900.5 7665 3825 942

39.37 9.78 19.61 79.36

5.51 1.76 2.35 14.28

also use different number of symbols for range and Doppler processing as discussed in [25]. 4. Conclusions In this manuscript, a dual function radar and communications system that used Gold or Kasami codes as communication sym-

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bols in an M-ary CSK system was examined. The main contribution of this work is demonstrating the ability to use a pseudo-random binary phase codes such as Gold and Kasami codes as a symbol alphabet in M-ary CSK communication system while using the same signal as a continuous wave radar signal with low probability of intercept (LPI) properties. The SER was evaluated for several code lengths via Monte Carlo simulations. The results compared favorably to the upper bound for the SER for MFSK. Due to the pseudo-random nature of the communication signal, it resembles a random binary phase coded noise radar signal. The radar waveform was evaluated using a symbol consisting of a 127-bit Gold coded sequence and a symbol consisting of a 255-bit small set Kasami coded sequence. Both waveforms demonstrated good range resolution and range side lobe levels that were comparable to those achieved using a RBPCR. The Doppler side lobes were also comparable to the RBPCR. Additionally, the use of QPSK modulation and subsequently a pseudo-random QPSK coded radar was also evaluated through simulations. This method provided satisfactory performance, although slightly higher range side lobe levels were present and Doppler side lobes levels of approximately −17 dB existed for the 255-bit Kasami coded symbol that was presented. One potential application of this concept is its use in naval operations during restricted EMCON conditions. For instance, during naval strike group operations, this conceptual system would allow one ship to conduct LPI radar surveillance of the battle space while relaying track data using the Gold or Kasami code shift keying communications. The use of frequency division multiplexing with orthogonal frequency allocations could allow multiple users to communicate; however, the complexity of the system would increase as a result. The use of pulse shaping such as use of a Hamming, Hanning, or Blackman window can be used to decrease the Doppler side lobes. The range side lobes may also be reduced through various filtering techniques described in [35–37]. Future work will evaluate the impact of applying various methods of reducing Doppler and range side lobe levels. Additionally, evaluating the use CDMA waveforms in dual function communications and radar system is a potential area of future research. Acknowledgment The authors would like to thank CDR (ret) Zachary Staples, USN, Director of the Center for Cyber-Warfare at Naval Postgraduate School for supporting this research effort. References [1] A. Hassanien, M.G. Amin, Y.D. Zhang, F. Ahmad, Signaling strategies for dualfunction radar communications: an overview, IEEE Aerosp. Electron. Syst. Mag. 31 (10) (2016) 36–45, https://doi.org/10.1109/MAES.2016.150225. [2] Z. Khan, J.J. Lehtomaki, R. Vuohtoniemi, E. Hossain, L.A. Dasilva, On opportunistic spectrum access in radar bands: lessons learned from measurement of weather radar signals, IEEE Wirel. Commun. 23 (3) (2016) 40–48, https:// doi.org/10.1109/MWC.2016.7498073. [3] Z. Khan, J.J. Lehtomaki, S.I. Iellamo, R. Vuohtoniemi, E. Hossain, Z. Han, IoT connectivity in radar bands: a shared access model based on spectrum measurements, IEEE Commun. Mag. 55 (2) (2017) 88–96, https://doi.org/10.1109/ MCOM.2017.1600444CM. [4] S.S. Raymond, A. Abubakari, H.S. Jo, Coexistence of power-controlled cellular networks with rotating radar, IEEE J. Sel. Areas Commun. 34 (10) (2016) 2605–2616, https://doi.org/10.1109/JSAC.2016.2605978. [5] H.A. Safavi-Naeini, S. Roy, S. Ashrafi, Spectrum sharing of radar and Wi-Fi networks: the sensing/throughput tradeoff, IEEE Trans. Cogn. Commun. Netw. 1 (4) (2015) 372–382, https://doi.org/10.1109/TCCN.2016.2557338. [6] H. Deng, B. Himed, Interference mitigation processing for spectrum-sharing between radar and wireless communications systems, IEEE Trans. Aerosp. Electron. Syst. 49 (3) (2013) 1911–1919, https://doi.org/10.1109/TAES.2013. 6558027. [7] A. Khawar, A. Abdelhadi, T.C. Clancy, Coexistence analysis between radar and cellular system in LoS channel, IEEE Antennas Wirel. Propag. Lett. 15 (2016) 972–975, https://doi.org/10.1109/LAWP.2015.2487368.

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Thomas W. Tedesso is an Assistant Professor at the United States Naval Academy, Annapolis, MD, serving on active duty in the United States Navy. He received a B.S. in Electrical Engineering from Illinois Institute of Technology, Chicago, IL in May 1990, a M.S. in Electrical Engineering from the Naval Postgraduate School, Monterey, CA, in Mar. 1998, and was awarded

a Ph.D. in Electrical Engineering from the Naval Postgraduate School, Monterey, CA, in Dec. 2013. Prior to commencing his doctoral studies in September 2010, he served in various assignments both ashore and afloat as a surface warfare officer trained in naval nuclear propulsion. Ric Romero received the B.S.E.E. degree from Purdue University, in 1999, the M.S.E.E. degree from the University of Southern California, in 2004, and the Ph.D. degree in Electrical and Computer Engineering from the University of Arizona, in 2010. He was a Senior Multidisciplined Engineer II with Raytheon Missile Systems, Tucson, AZ, from 1999 to 2010. He is currently an Associate Professor with the Department of Electrical and Computer Engineering, Naval Postgraduate School, Monterey, CA. His research interests are in the general areas of radar, sensor information processing, and communications.