Phase coded waveforms for integrated sensing and communication systems

In an integrated radar and communication system, the filter output of each pulse of the integrated radar and communication waveform usually has high sidelobe level (SLL) and signal-to-noise ratio (SNR) loss as well as serious range sidelobe modulation (RSM). To solve these problems, a joint weighted optimization (JWO) method is proposed to design the filters. In this method, the filters for different integrated radar and communication waveforms are designed by jointly minimizing the RSM, SNR loss, and SLL according to different practical demands. In terms of the RSM, SNR loss, and SLL, the performance of the designed filters is tunable by reasonably changing the weight factors. Finally, several numerical results are presented to verify the effectiveness of the proposed method.

We present a novel approach to the problem of dual-functional radar and communication (DFRC) waveform design with adjustable peak-to-average power ratio (PAPR), while minimizing the multi-user communication interference and maintaining a similarity constraint towards a radar chirp signal. The approach is applicable to generic radar chirp signals and for different constellation sizes. We formulate the waveform design problem as a non convex optimization problem. As a solution, we adopt the alternating direction method of multipliers (ADMM), hence iterating towards a stable waveform for both radar and communication purposes. Additionally, we prove convergence of the proposed method and analyze its computational complexity. Moreover, we offer an extended version of the method to cope with imperfect channel state information (CSI). Finally, we demonstrate its superior performance through simulations, in comparison to state-of-the-art radar-communication waveform designs.

Microwave/millimeter-wave photonics is playing a prominent role in overcoming the challenges of RF signal generation and processing. This evolving technology has many advantages, such as RF carrier stability and broad operating bandwidth, and is applicable to a wide range of civil and military applications such as 5G communication networks, radar/jammer systems, and medical imaging. In this work, we leverage the multidimensional capabilities of microwave photonics in order to generate multi-band/multi-mode radar signals for multi-purpose applications. Our proposed system can generate up to five radar bands, simultaneously, with different modulation bandwidths, without hardware modifications. Additionally, various radar waveforms can be transmitted, simultaneously, over the corresponding radar bands. The RF radar signals are generated optically using a reconfigurable frequency comb source, which reduces the system cost significantly. The stability of the RF carriers is experimentally tested and compared with that of the mode-locked-loop-based laser sources, wherein a comparable performance is observed. Experimental results show the generation of four radar waveforms, including frequency modulated waveforms (pulsed linear frequency modulation and frequency modulated continuous wave) and polyphase codes (Barker-11 and Barker-13). Moreover, five carrier frequencies are used to transmit the various radar modulation schemes. These are 5.25, 9.325, 16.1, 26.4, and 28.15 GHz RF carriers. The signal quality is measured experimentally, and high signal-to-noise ratio (SNR) of 35, 30, 30, 25, and 20 dB SNR was observed in the C-, X-, Ku-, K-, and Ka-bands, respectively.

Phase modulation with an analytic signal, which is a Gaussian random process, is examined in order to determine the amount of spectrum conservation that may be achieved by using single-sideband phase modulation (SSB-PM) rather than conventional phase modulation (PM). The autocorrelation function is derived and found to be an analytic signal in terms of the autocorrelation function of the actual modulating signal and its Hilbert transform. When the modulating signal strength is very low, the sideband spectral distribution is the same as that of the actual modulating signal or single-sideband amplitude modulation. As the modulating signal mean-square value is increased, the sideband spectrum broadens and approaches a Gaussian shape. The average power output of an SSB-PM system increases exponentially with input modulating signal strength, while the carrier power remains constant. For the same modulating signal mean-square value, a greater fraction of power is in the one sideband of an SSB-PM system than in the two sidebands of conventional PM. Single-sideband phase or frequency modulation always effectuates spectrum conservation in the continuum when it is compared with conventional phase or frequency modulation on the basis of equal relative sideband power. A Fourier transform computer program is used to generate SSB-PM spectral distributions with varying modulating signal mean-square values, when the modulating signal spectrum is a low-pass rectangular spectrum, a narrowband pass spectrum, and the shape of an average voice spectrum. These examples illustrate the power series formulation of the output spectrum as well as the theoretical analysis of bandwidth.

The integration of sensing and communication functions in one platform has become a pivotal use case in future communication systems. This research investigated the optimal integrated sensing and communication (ISAC) waveforms for the purpose of vital signs detection. In order to incorporate both functions in the system and make it favorable for sensing the micro-doppler effect associated with vital signs, orthogonal frequency division multiplexing (OFDM) and phase-coded frequency modulated continuous wave (PC-FMCW) signals were adopted and compared, and the performances were evaluated against the system based on the classic frequency modulated continuous wave (FMCW). Several phase coded FMCW signals have been investigated and the simulated results indicated that the Frank-coded PC-FMCW waveform exhibited an optimal performance for vital signs detection in a line-of-sight setting. The work is beneficial for search and rescue applications where high-performance sensing such as vital signs detection and limited communication capability is required.

This paper aims to detect and characterize a signal coming from frequency modulation continuous wave radars. The radar signals are made of piecewise linear frequency modulations. The maximum chirplet transform (MCT), a simplification of the chirplet transform is proposed. A detection of the relevant maximum chirplets is proposed based on iterative masking, an iterative detection followed by window subtraction that does not require the recomputation of the spectrum. This detection is designed to provide a sparse subset of maximum chirplet coefficients. The chirplets are then gathered into linear chirps whose starting time, length, and chirprate are estimated. These chirps are then gathered again back into the different frequency modulation continuous wave signals, ready to be classified. An illustration is provided on synthetic data.

Internet of Things (IoT) based voice interaction system, as a new artificial intelligence application, provides a new human–computer interaction mode. The more intelligent and efficient communication approach poses greater challenges to the semantic understanding module in the system. Facing with the complex and diverse interactive scenarios in practical applications, the academia and the industry urgently need more powerful Natural Language Understanding (NLU) methods as support. Intent Detection and Slot Filling joint task, as one of the core sub-tasks in NLU, has been widely used in different human–computer interaction scenarios. In the current era of deep learning, the joint task of Intent Detection and Slot Filling has also changed from previous rule-based methods to deep learning-based methods. It is an important problem to explore how to realize the models of these tasks to be refined and targeted designed, and to make the Intent Detection task better serve the improvement of precision of Slot Filling task by connecting the before and after tasks. It has great significance for building a more humanized IoT voice interaction system. In this study, we designed two joint models to realize Intent Detection and Slot Filling joint task. For the Intent Detection type task, one is based on BiGRU-Att-CapsuleNet (hybrid-based model) and the other is based on the RCNN model. Both methods use the BiGRU-CRF model for the Slot Filling type task. The hybrid-based model can enhance the semantic capture capability of a single model. And by combining specialized models built independently for each task to achieve a complete joint task, it can be better to achieve optimal performance on each task. This study also carried out detailed comparative experiments of tasks and joint tasks on multiple datasets. Experiments show that the joint models have achieved competitive results in 7 typical datasets included in multiple scenarios in English and Chinese compared with other models.

Data acquisition and Signal Processing is an important part of frequency modulated continuous wave (FMCW) radar system. In recent year P2ET-LIPI was developing FMCW navigation radar system in portable size. The main component of data acquisition for navigation radar is highspeed Analog to Digital Conversion (ADC) USB-2020 board and signal processing algorithm has been developed using Visual C# 2015 Community Edition. USB-2020 board has two channel ADC on board with 12 bits resolution and operated in a burst-io mode to get maximum sampling rate at 20 MS/s. A timing generator for synchronization between ADC and linear frequency modulation (LFM) chirp generator is developed using Complex Programmable Logic Device (CPLD) Max II series based on VHSIC hardware description language (VHDL). Signal processing unit consists of windowing function to reduce side- lobe suppression, Fast Fourier Transform (FFT) function to get range information and adaptive threshold using three algorithms of Constant False Alarm Rate (CFAR): Cell Averaging (CA), Order Statistic (OS) and Variable Index (VI) CFAR. The experiment shows that the data acquisition module can capture In-phase and Quadrature (I/Q) beat signal and signal processing algorithm can detect object/target from the noise.

In radar electronic warfare (EW) reconnaissance, radio frequency (RF) is an important parameter for describing the received pulse, and it is usually used in sorting and identifying radar signals. In order to achieve different detection purposes, different modulations are used in intra-pulse and interpulse radar signals. It is an important frequency modulation mode in radar signals for interpulse frequency modulation, which describes the characteristics of dynamic changes of radar pulse signals. However, it is difficult to describe these characteristics effectively by only using Pulse Description Word(PDW). In this letter, a novel feature, based on symbolization and entropy, is proposed to characterize interpulse frequency modulation characteristics of radar signals. Simulation results show that the proposed feature not only have an excellent performance of describing interpulse RF modulation radar signals, but is also insensitive to the environment with a certain rate of pulses missing and spurious pulses. Besides, in terms of time complexity, it also has a satisfactory performance.

Phase noise can severely degrade the radar performances by producing strong sidelobes which may mask small targets. Reducing those sidelobes by improving the radar analog front-end severely increases the system complexity. Another approach consists in developing waveforms more robust to phase noise. Even if the phase noise phenomenon is well known, it has been intensively investigated only in Frequency Modulated Continuous Wave (FMCW) radars, not so much in Phase Modulated Con-tinuous Wave (PMCW) radars. In this paper, we will provide a detailed analysis of the impact of phase noise on FMCW radars and on different code sequences for PMCW radars. This analysis will be used to compare the impact of phase noise on different waveforms. Both range profile and Doppler profile will be investigated. We will show that radar waveforms can be designed to provide low sidelobes in presence of phase noise. Our model will be validated by simulation.

We propose a novel space-time waveform coding (STWC) scheme for joint radar and wireless communications (RadCom). In particular, we consider a frequency-modulated continuous-wave (FMCW) multiple-input multiple-output (MIMO) radar for near-range to medium-range radar applications. In order to establish the required orthogonal transmit signals, up- and down-chirp FMCW waveforms are combined with Alamouti space-time coding across two transmit antennas. We demonstrate that, from a radar perspective, the cross-ambiguity function is improved significantly by the orthogonal Alamouti code, while the FMCW waveforms ensure robustness in the presence of Doppler shifts. Regarding the communications part, the generic orthogonality of the Alamouti code allows us to embed random information symbols within the radar signal, enabling wireless communications in the 100 kb/s regime. To this end, we propose a suitable communications receiver algorithm for multiple antennas with corresponding maximum-ratio combining, which is able to extract the embedded information symbols while acquiring spatial diversity gains.

We present a method to create an RF MEMS oscillator with continuous control of the output phase and frequency. When the weakly nonlinear oscillating system becomes synchronized with an imposed sinusoidal force of close frequency, the resonator frequency can be detuned with a DC bias on a resistive actuator to produce an easily controlled phase differential between the injected signal and the resonator feedback. We demonstrate a 26 MHz MEMS oscillator with frequency tunability of 0.3% and phase tunability of 200/spl deg/. By modulating the Joule heat dissipated in the structure, a 26 MHz carrier frequency was either frequency modulated by a 30 kHz baseband signal with a modulation depth of 15 kHz, or phase modulated by a 20 kHz baseband signal with a modulation depth of 160/spl deg/.

The emergence of 6G wireless networks demands solutions that seamlessly integrate communication and sensing. This letter proposes a novel waveform design for joint sensing and communication (JSAC) systems, combining single-carrier interleaved frequency division multiplexing (SC-IFDM), a 5G communication candidate signal, with frequency modulated continuous wave (FMCW), widely used for sensing. The proposed waveform leverages the sparse nature of FMCW within SC-IFDM to achieve orthogonal integration in three steps: SC-IFDM symbols are allocated alongside the sparse FMCW, followed by the SC-IFDM transform into the time domain, and a cyclic prefix (CP) is applied in which phase shifts are introduced to the FMCW. Additionally, an enhanced channel estimation method is incorporated to boost system performance. Simulation results demonstrate the proposed waveform’s ability to deliver high-resolution sensing and superior communication performance, surpassing traditional multicarrier designs.

From the perspective of radar signal processing, the pulse-Doppler radar signal model is mostly based on the stop-and-go model due to the short pulse propagation time. Unlike the pulse-Doppler radar, the frequency modulated continuous wave (FMCW) radar takes a long time in the process of signal transmission to echo reception. During this period, the target cannot be considered to be stationary during the acquisition of the entire sweep echo, so the stop-and-go assumption in the FMCW system is no longer valid, which means that the target's motion related to the fast time must be taken into account. In the inverse synthetic aperture radar (ISAR) imaging scenario of high-speed maneuvering targets, the frequency offset correction introduced by the target's motion becomes reasonably complicated that it is difficult to restore the usual ISAR signal processing. In this work, a new method based on phase retrieval and image contrast-based autofocus (ICBA) is proposed to address the complex problem of motion compensation for FMCW ISAR systems. To cope with the fast time-varying characteristics of the phase error and the higher number of phase terms relative to pulsed radars, the proposed algorithm performs fine compensation with higher accuracy, resulting in high-resolution and autofocus imaging. Experimental results demonstrate the effectiveness of the proposed method.

In this paper proposed is a cost-efficient signal processing algorithm of a frequency modulation continuous wave (FMCW) radar for the close range under indoor environments. Recently, the use of an FMCW radar has been expanded to short distance from long distance due to easy production and inexpensive designing costs. In order to obtain satisfying resolution of the close range radar, it still requires a wide modulation bandwidth, which results in high costing wideband RF devices. This paper proposes a cost-efficient signal processing method using correlations between a reflected signal in frequency-domain and a lookup table which holds the frequency information depending on distances. The proposed algorithm shows the similar performance to a wideband system just by updating a firmware of low costing narrowband RF FMCW radar devices without additional hardware modification.