Chirp Radar Research Articles

On Integrated Sensing and Communication Waveforms With Tunable PAPR

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.

Influence of the range Doppler coupling error on the characteristics of second-order filters

This paper mainly considers a growing-memory filter for tracking an object moving with constant acceleration and detected by chirp radar. Chirp radars employ linear frequency modulated (LFM) waveforms for object tracking which yields a displacement of measured position from a true range of moving objects. This effect may enable better track accuracy in range. The second order degree polynomial describes coordinates law for a constantly accelerating maneuvering object. The issues of lag errors, covariance matrix of the filtered state vectors, impulse responses and Kalman gains are discussed. For example, the growing-memory filter is most often used for initiating track. The growing-memory filter is derived in recursive and non-recursive form based on least-squares. It is shown that the growing-memory filter estimating a true object range (with the range-Doppler coupling coefficient) can be represented by the growing-memory filter estimating a biased object range (without the range-Doppler coupling coefficient) and compensating the estimated biased range by the estimated the range-Doppler coupling error. Expressions giving an interrelation between lag errors, covariance matrix of the filtered state vectors, impulse responses and Kalman gains of growing-memory filters estimating true and biased range of moving objects are derived.

An Experimental Study of Radar-Centric Transmission for Integrated Sensing and Communications

This study proposes a dual-function radar and communication (DFRC) system that utilizes radar transmission parameters as modulation indexes to transmit data to the users while performing radar sensing as its primary function. The proposed technique exploits index modulation (IM) using the center frequency of radar chirps, their bandwidths, and polarization states as indexes to modulate the communication data within each radar chirp. By utilizing the combination of these indexes, the proposed DFRC system can reach up to 17 Mb/s throughput, while observing a robust radar performance. Through our experimental study, we also reveal the trade-off between the radar sensing performance and communication data rate, depending on the radar waveform parameters selected in the DFRC system. This study also demonstrates the implementation of the proposed DFRC system and presents its real-time over-the-air experimental measurements. Consequently, the simulation results are verified by real-time over-the-air experiments, where ARESTOR, a high-speed signal processing and experimental radar platform, has been employed.

Deep Learning-Based Link Configuration for Radar-Aided Multiuser mmWave Vehicle-to-Infrastructure Communication

Configuring millimeter wave links following a conventional beam training protocol, as the one proposed in the current cellular standard, introduces a large communication overhead, especially relevant in vehicular systems, where the channels are highly dynamic. In this paper, we propose the use of a passive radar array to sense automotive radar transmissions coming from multiple vehicles on the road, and a radar processing chain that provides information about a reduced set of candidate beams for the links between the road-infrastructure and each one of the vehicles. This prior information can be later leveraged by the beam training protocol to significantly reduce overhead. The radar processing chain estimates both the timing and chirp rates of the radar signals, isolates the individual signals by filtering out interfering radar chirps, and estimates the spatial covariance of each individual radar transmission. Then, a deep network is used to translate features of these radar spatial covariances into features of the communication spatial covariances, by learning the intricate mapping between radar and communication channels, in both line-of-sight and non-line-of-sight settings. The communication rates and outage probabilities of this approach are compared against exhaustive search and pure radar-aided beam training methods (without deep learning-based mapping), and evaluated on multi-user channels simulated by ray tracing. Results show that: (i) the proposed processing chain can reliably isolate the spatial covariances for individual radars, and (ii) the radar-to-communications translation strategy based on deep learning provides a significant improvement over pure radar-aided methods in both LOS and NLOS channels.

Countering self-protection interrupted sampling repeater jammer against chirp radar

AbstractInterrupted sampling repeater jammer generates multiple false targets to confuse chirp radar systems. In practical situations, maintaining separation between true target echo and jamming signal is not possible because the jamming pulses and the true target echo are overlapping in both time and frequency domains. A new anti-jamming technique against interrupted sampling jamming of self-protection repeater jammer is proposed without the knowledge of the jamming parameters. The proposed technique is based on fractional Fourier transform that can separate the overlapping true target echo and jamming pulses in the fractional domain, and then the resulting pulses are returned to the time domain, the true target can be easily distinguished from the false ones because the jamming pulses lag behind the true target echo by the jammer's delay. The theoretical analysis and simulation results demonstrate the efficiency and validity of the proposed technique.

Optimization-Free Filter and Matched-Filter Design through Spatial and Temporal Soft Switching of the Dielectric Constant

The problem of inverse design is rooted to the classical problem of inverse scattering. In general, these highly nonlinear and often ill-posed problems are solved via extensive optimization techniques. In this paper, we suggest an optimization-free method for the inverse design of a one-dimensional medium with spatially inhomogeneous dielectric constant $ϵ(z)$. In addition, we derive the governing equation of an analog problem---a time-dependent homogeneous medium---and use the same technique for inverse design of the temporal profile $ϵ(t)$ of a spatially homogeneous medium that is required to achieve a desired frequency response in $k$-space. Lastly, we use this optimization-free inversion approach to demonstrate the design of the reflection response such that the reflected wave undergoes a desired filtering, such as of Tchebychev type, differentiator, and a matched filter for chirp signal detection over additive Gaussian noise, which is of high potential significance in chirp radar and sonar applications.

Calibration of Wideband FMCW Polarimetric Radars Operating at Millimeter-Wave Frequencies

This article presents a comprehensive technique for calibrating wideband frequency-modulated continuous-wave (FMCW) fully polarimetric radars employing linear FM (LFM) signal chirps. A detailed system distortion model is developed that accounts for both polarimetric distortions and distortions caused by nonlinearities in the transmitted and received radar chirps over multiple polarization channels. Using the radar responses of two point targets at known distances from the radar, the calibration technique is able to estimate the range-dependent nonlinearities in phase and correct them for all targets at all ranges. This allows the radar to achieve its ideal range resolution. In addition, the calibration technique corrects for channel imbalances in the polarimetric radar using a metallic sphere of known diameter and any depolarizing target. Both numeric simulations and actual polarimetric radar measurements using a wideband FMCW radar operating over 76.5–82 GHz were used to validate the calibration technique.

An Anti-Jamming Method against Two-Dimensional Deception Jamming by Spatial Location Feature Recognition

Interrupted sampling repeater jamming (ISRJ) is an effective method for implementing deception jamming on chirp radars. By means of frequency-shifting jamming processing of the target echo signal and pulse compression during image processing, a group of false targets will appear in different spatial locations around the true target. Extracting the features of these false targets is complex and limited to existing countering methods against ISRJ. This paper proposes an anti-jamming method to identify the spatial location characteristics of two-dimensional deception false targets. By adjusting the parameters of the radar transmitted signal, the method simultaneously transmits the anti-jamming signal and carries out false target identification and elimination in the range and azimuth dimensions. Eventually, the optimal signal parameter design of the anti-jamming signal is obtained by comparing different anti-jamming strategies in the range dimension. The validity of the proposed method is proved by deducing the mathematical model between the spatial distribution characteristics of the false targets and the radar transmitted signal parameters and demonstrated by simulations.

Automotive interference statistics and their effect on radar detector

Millimetre-wave frequency-modulated continuous wave (FMCW) radars are at present widely deployed in the autonomous vehicles. The growing usage of such sensors, as a vital part of a robust future autonomous sensing system, sees the potential for significant increase in mutual interference and adverse effects on sensor operation. Effective target detection in the background of interference requires knowledge of the interference statistics. In the case that such statistics are found to be similar to that of additive white Gaussian noise (AWGN), then classical well-established detection techniques can be applied. Conversely, if statistics are found to be different, traditional techniques (matched filtering) will not be optimal. Here, a statistical analysis of mutual interference within an FMCW victim radar is presented. The majority of cases show a low correlation between the interference pulses received at the victim radar, with close to a Gaussian distribution. Some specific cases show a high correlation between the interference pulses in the victim radar chirps with a sinusoidal-like distribution, which degrades the victim radar’s detection performance. The presented analysis is validated by experimental data for various interference cases.

Intelligent Recognition of Chirp Radar Deceptive Jamming Based on Multi-Pulse Information Fusion.

The perception of jamming types is very important for protecting our radar in complex electromagnetic environments. Radar active deceptive jamming based on digital radio frequency memory (DRFM) has a high coherence with the target echo, which confuses the information of the target echo and achieves the effect of hiding the real target. Traditional deceptive jamming recognition methods need to extract complex features and artificially set classification thresholds, which is inefficient. The existing neural network-based jamming identification methods still follow the pattern of signal modulation-type identification, so there are fewer types of jamming that can be identified, and the identification accuracy is low in the case of low jamming-to-noise ratios (JNR). This paper studies the input of jamming recognition networks and proposes an improved intelligent identification method for chirp radar deceptive jamming. This method fuses three short-time Fourier transform time–frequency graphs disturbed by three consecutive pulse periods into a new graph as the input of the convolutional neural network (CNN). Using a CNN to classify the time–frequency image has realized the recognition of a variety of common deceptive jamming techniques. Similarly, by changing the network input, the original signal is used to replace the echo signal, which improves the accuracy of the jamming recognition in the case of a low JNR.

Countering self‐protection smeared spectrum jamming against chirp radars

Countering self‐protection smeared spectrum jamming against chirp radars

A Modular MIMO Millimeter-Wave Imaging Radar System for Space Applications and Its Components

This article presents the design and prototyping of components for a modular multiple-input-multiple-output (MIMO) millimeter-wave radar for space applications. A single radar panel consists of 8 transmitters (TX) and 8 receivers (RX), which can be placed several times on the satellite to realize application-specific radar apertures and hence different cross-range resolutions. The radar chirp signals are generated by SiGe:C BiCMOS direct-digital-synthesizers (DDS) in the frequency range of 1 to 10.5GHz with a chirp repetition rate of 30dB gain with noise figure values of 9dB, respectively. The MIMO radar utilizes patch antenna arrays on organic multilayer printed circuit boards (PCB) with 18dBi gain and 18∘ half power beamwidth (HPBW). Generation of power supply and control signals, analog-to-digital conversion (ADC), and radar signal processing are provided centrally to each panel. The radar supports detection and tracking of satellites in distances up to 1000m and image generation up to 20m, which is required to support orbital maneuvers like satellite rendezvous and docking for non-cooperative satellites.

Photonic fractional Fourier transformer for chirp radar with ghost target elimination.

For the first time, to the best of our knowledge, we propose a photonic fractional Fourier transformer (PFrFTer), which is used in chirp radar for detecting multiple non-cooperative targets. Based on photonic rotation of the time-frequency plane, the optimal fractional Fourier domain is formed, and the received broadband chirp signals are projected on it, where they behave as impulses. Moreover, through manipulating the fractional Fourier transform spectrum, the PFrFTer contributes to the cancellation of two ghost target sources, so that the ghost targets in multiple-target circumstances are removed. The simulation and experimental results show that the proposed PFrFTer can adapt to multiple non-cooperative targets environments and is immune to ghost targets at optimal working conditions, which agrees well with the theoretical analysis.

Improving Passive Radar Target Recognition Using a Convolution Composite WiFi Preamble

This paper studies indoor passive radar target recognition and presents a convolution composite scheme involving a WiFi long preamble and radar chirp signal to improve target recognition resolution. In addition, we present trials of different-sized ball recognition and human standing/lying recognition by using the convolution preamble based on finite-difference-time-domain (FDTD) calculations. The results show that the channel estimation anti-fading of the convolution composite preamble is much better than that of the time-domain composite based on receiver cancellation. Hence, more radar chirp constituents can be convolved, the recognition resolution is notably improved, and the convolved signal has the same or even a slightly better resolution than the chirp signal which is in the conventional multiplexing mode. The given method may be applied to device-free people counting to distinguish adults and children and to detect elderly people falling in bathrooms, among other health monitoring applications.

Enhancement of Matched Filter Response for Chirp Radar Signals using Signal Recovery Technique

The matched filter is one among many effective techniques used to maximize the signal –to- noise ratio (SNR) of chirp radar signals. Besides this enhancement in SNR, it has a drawback due to sidelobe levels which degrade the filter response. There are many additional techniques which reduce these levels such as window techniques and inverse filter. In this paper, a new approach is utilized to completely cancel the level of matched filter side lobes based on the signal recovery of the compressive sensing (CS) theory. The reconstruction process of CS is based on the CAMP algorithm which applied to the response of the matched filter. The recovered chirp radar signals are achieved with completely side lobes cancellation compared to the traditional side lobe reduction technique based on the widow method. The comparison between the proposed and traditional methods is achieved according to the detection performance using Receiver Operating Characteristic (ROC) curve. Besides the detection performance, a resolution in the range is another comparison aspect between these algorithms.

Technique to Counter Improved Active Echo Cancellation Based on ISRJ With Frequency Shifting

Interrupted-sampling repeater jamming (ISRJ) is an effective method to jam chirp radars. Furthermore, by modulating ISRJ repeater parameters, ISRJ achieves radar echo cancellation using the ISRJ false target that synchronizes with the true target echo, with the same amplitude and inverted phase. Recently, an improved method based on both ISRJ and frequency shifting modulation has been proposed to protect the true target more effectively in the presence of amplitude mismatch of cancellation signal and true target echo. In this paper, an anti-jamming technique based on waveform agility is proposed to counter this improved cancellation method. This technique not only eliminates the effect of the ISRJ echo canceler but also makes the true target power higher than that of the false ones. Therefore, it can be discriminated from the jamming ones easily. The theoretical analysis of this technique is presented, and its effectiveness is confirmed by MATLAB simulation.

Ultrawideband Synthesis for High-Range-Resolution Software-Defined Radar

This article presents a design for implementing an ultrawideband (UWB) software-defined radar (SDRadar) using a bandwidth reconstruction technique, called frequency stacking, for a stepped frequency signal to create a synthetic wideband waveform (SWW). Practical methods of overcoming traditional limitations of SDRadar and stepped chirp radar are introduced, and the performance is demonstrated using a commercial battery-powered universal software radio peripheral (USRP) software-defined radio (SDR). Application-specific considerations are made and performance tradeoffs are demonstrated. Furthermore, the method is shown to be the coherence solution for otherwise noncoherent low-cost communications’ SDR systems. The proposed design has multiple applications in low-cost, reconfigurable ground-penetrating radar (GPR) and small unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) platforms.

Design Considerations for Integrated Radar Chirp Synthesizers

Design Considerations for Integrated Radar Chirp Synthesizers

Multifunction Radio Frequency Photonic Array With Beam-Space Down-Converting Receiver

A multifunction photonic beam-space array processor is shown to generate the beam space of an X -band array. Subsequent down-conversion of desired beams is performed via introduction of an optical local oscillator and high-speed photodetectors at the processor output. A separate optical path is used to “image” the full field of view of the input array for real-time angle-of-arrival estimation. Finally, experimental results showing simultaneous processing of output beams for a radar waveform and an in-band communications signal are presented. The recovery of a 10-MHz bandwidth, quaternary phase-shift keying communications signal with a nominal error vector magnitude of 15.5% is performed via a vector signal analyzer, whereas a custom digital beam-space beam-forming processor is shown to process the same beam data to recover a 100-MHz chirp radar waveform while simultaneously canceling the in-band communications signal by approximately 20 dB via an adaptive spatial null.

OFDM chirp radar for adaptive target detection in low grazing angle

Low-altitude target detection is of great importance in radar applications, especially for military radar to counter the targets penetrated from low grazing angles. However, it is a challenge to detect the targets in low grazing angle area due to severe multipath reflection effects. In this study, the authors propose orthogonal frequency division multiplexing (OFDM) chirp waveform for target detection in low grazing angle region. The OFDM chirp waveform has better peak-to-average-power ratio level and provides larger time-bandwidth product than that of conventional OFDM waveform, which is beneficial for target detection. Two different radar schemes, namely, OFDM chirp radar and OFDM chirp multiple-input multiple-output (MIMO) radar, are studied under the Earth's curvature geometry model with the consideration of realistic multipath reflection effects. The generalised likelihood ratio test algorithm is developed by jointly exploiting the advantages of OFDM chirp waveform and MIMO configuration in increased degrees of freedom. In addition, an adaptive algorithm is further applied to enhance the target detection performance. All proposed schemes are verified by numerical results.