Random Pulse Repetition Interval Research Articles

An Off-Grid Compressive Sensing Algorithm Based on Sparse Bayesian Learning for RFPA Radar

In the application of Compressive Sensing (CS) theory for sidelobe suppression in Random Frequency and Pulse Repetition Interval Agile (RFPA) radar, the off−grid issues affect the performance of target parameter estimation in RFPA radar. Therefore, to address this issue, this paper presents an off−grid CS algorithm named Refinement and Generalized Double Pareto (GDP) distribution based on Sparse Bayesian Learning (RGDP−SBL) for RFPA radar that utilizes a coarse−to−fine grid refinement approach, allowing precise and cost−effective signal recovery while mitigating the impact of off−grid issues on target parameter estimation. To obtain a high-precision signal recovery, especially in scenarios involving closely spaced targets, the RGDP−SBL algorithm makes use of a three−level hierarchical prior model. Furthermore, the RGDP−SBL algorithm efficiently utilizes diagonal elements during the coarse search and exploits the convexity of the grid energy curve during the fine search, therefore significantly reducing computational complexity. Simulation results demonstrate that the RGDP−SBL algorithm significantly improves signal recovery performance while maintaining low computational complexity in multiple scenarios for RFPA radar.

Anti‐interrupted sampling repeater jamming method for random pulse repetition interval and intra‐pulse frequency agile radar

AbstractInterrupted sampling repeater jamming can produce numerous active false targets with high fidelity, which is a significant challenge for coherent pulse radar. This poses a threat to the effectiveness of anti‐jamming technology, such as time‐frequency analysis and frequency agility for conventional constant pulse repetition interval (PRI) radar, which will render the radar inoperable to detect and track the actual target. A random PRI and intra‐pulse frequency agile radar waveform with low interception properties is proposed, which can effectively restrict the acquisition of radar waveform parameters by the jammer, destroy the coherence of jamming signals, and capture the range‐dimensional centroid feature of the echo. Accordingly, a jamming identification method based on the scale constrained Gaussian mixture model and an entity radar target energe recovery algorithm based on the neighbourhood weighted maximum entropy are proposed for target detection. Theoretical analysis and simulation experiments demonstrate the effectiveness of the proposal.

Implications of Diversified Doppler for Random PRI Radar

This paper seeks to expand the fundamental understanding of random pulse repetition interval (PRI) staggering radar by formulating a physically meaningful “Doppler manifold” signal model that incorporates slow-time coding and is examined in the context of monostatic, multiple-time-around (MTA) scattering, and multiple-input multiple-output (MIMO) configurations. In so doing, it is found that an intrinsic “range decoherence” effect arises for the MTA and MIMO cases, thereby expanding the means through which separability can be achieved, albeit with rather different degrees of “decoherence amplification”. Moreover, a closed-form solution for the average Doppler response due to random staggering is derived, yielding guidance on the degree necessary to suppress Doppler ambiguities.

Multi-Timeslot Wide-Gap Frequency-Hopping RFPA Signal and Its Sidelobe Suppression

Random frequency and pulse repetition interval agile (RFPA) signals have excellent anti-jamming ability and achieve low probability of intercept (LPI), making them promising for applications in radar systems. However, their matched filter (MF) outputs suffer from random range-velocity sidelobes. In the range dimension, these sidelobes can be classified into two categories: the distant sidelobe floor spread out beyond the minimum interval between pulses, and the near sidelobe plateau confined within about one pulsewidth. These sidelobes seriously degrade the target detection capability of RFPA signals. To address this issue, we propose the concept of a multi-timeslot wide-gap frequency-hopping sequence (multi-timeslot WGFHS) and use it in the design of RFPA signals. In doing so, the distant sidelobes are easily suppressed with a simple low-pass filter (LPF) in the receiver if the parameters of the multi-timeslot WGFHS are chosen properly, while the remaining near sidelobes are suppressed by the iterative adaptive approach based on matched filter outputs (MF-IAA). Simulation results show that the proposed method can effectively suppress the sidelobes of RFPA signals, accurately recover the range-velocity images, and successfully detect weak targets in the presence of strong targets or clutter.

Maneuvering Target Coherent Integration and Detection in PRI-Staggered Radar Systems

As for a new-style radar, the random pulse repetition interval (PRI) pulse waveform may be transmitted, and then the target Doppler parameter estimation precision and detection ability by using the conventional techniques may be invalid due to the irregular signal sampling. To solve these problems, this letter proposes a simple, yet effective and quasi-optimal coherent integration method with random pulse resampling. The proposed method first reconstructs the nonuniformly sampled signal into a uniform grid in the range frequency domain based on the modified sinc interpolation theory. Then, a matched filtering function related to the target chirp parameter is constructed in order to eliminate the residual coupling between range and azimuth. Finally, a moving target can be well imaged after performing the target motion compensation.

Maneuvering target detection in random pulse repetition interval radar via resampling-keystone transform

With good electronic counter-countermeasures capability, random pulse repetition interval (PRI) radars receive increasing attention recently. However, the problem of maneuvering target detection in random PRI radars is rarely studied yet. In this problem, the difficulty lies in not only the range migration (RM) and Doppler frequency migration (DFM) effects but also the non-uniform sampling pulses. This paper proposes a novel algorithm for this problem. In the proposed algorithm, we first combine the non-uniform resampling operation and the keystone transform to propose the resampling-keystone transform, which can eliminate the RM and resample the non-uniform sampling pulses into uniform ones in one step. Then, the dechirp process, whose implementation can benefit from the fast Fourier transform, is employed to accomplish coherent integration for target detection by compensating the DFM. The proposed algorithm is applicable for both single-target and multi-target scenarios. Besides, the available integration time and computational complexity of the proposed algorithm are analyzed. Finally, simulation results are given to show that the proposed algorithm can approach the optimal detection performance with a much lower computational cost than the well-known generalized Radon Fourier transform.

Coherent integration algorithm for random pulse repetition interval radar based on iterative adaptive approach

An iterative adaptive approach (IAA) based algorithm is presented to realise coherent integration for the random pulse repetition interval radar. The proposed method firstly removes the effect of Doppler ambiguity via phase compensation, and then accomplishes target focusing via conducting the azimuth IAA and range inverse fast Fourier transform. Theoretical analysis and numerical experiments have verified the effectiveness of the proposed method.

Ambiguity Function Analysis of Random Frequency and PRI Agile Signals

Random frequency and pulse repetition interval (PRI) agile (RFPA) signals bring excellent performance of electronic counter-countermeasures to radar systems and have been received considerable attention in recent years. However, the research on their ambiguity function (AF) is not comprehensive. In this article, the analytical expressions of the AF expectation and variance are given. According to the expressions, the direct relationships between the key metrics of the AF and the waveform parameters of RFPA signals are specified. The results in this article are verified by Monte Carlo simulations and provide some insights into RFPA waveform design.

Weak maneuvering target detection in random pulse repetition interval radar

The range migration (RM) and Doppler frequency migration (DFM) are the two major problems faced by radar maneuvering target detection. Unlike the existing algorithms which focus on the correction of RM and DFM in the fixed pulse repetition interval (PRI) system, this paper proposes a novel method which can further realize coherent integration in the random PRI system. The proposed method firstly conducts the multi-dimensional search for the maneuvering target's trajectory, then compensates DFM and realizes coherent integration via the nonuniform polynomial sparse Fourier transform (NUPSFT). As a linear algorithm, the proposed method can detect multiple weak targets without generating any cross term. Moreover, a high processing efficiency can be obtained thanks to the application of sparse Fourier transform (SFT). Both theoretical analysis and simulation results have validated the effectiveness of the proposed method.

Fast coherent integration method for moving target detection with random PRI variation

This Letter addresses the coherent integration problem for the moving target detection in a pulse repetition interval (PRI)-staggered radar system. Due to the random sampling, the complex coupling effects between range and azimuth will severely degrade the target parameter estimation and coherent integration performance. To deal with this issue, a fast coherent integration detection method with random azimuth sampling is proposed, where range migration is firstly compensated by applying the range-frequency reversal transform. Then, the random phase fluctuation caused by the staggered PRI can be efficiently removed by applying the non-uniform FFT technique. Finally, a moving target can be well focused. Simulated results are provided to validate the effectiveness of the proposed algorithm.

Coherent integration method for random pulse repetition interval radar based on non‐uniform keystone transform and non‐uniform fast Fourier transform

In order to achieve weak target detection, the range migration and Doppler frequency spread induced by the target motion within the coherent processing interval should be compensated to focus the target energy in a certain range-Doppler cell. This article proposes a new integration method based on non-uniform Keystone transform and non-uniform fast Fourier transform (NUFFT) for random pulse repetition interval (PRI) radar. In this method, non-uniform Keystone transform is applied to correct the linear range migration. After that, the acceleration is estimated by dechirp process and the Doppler frequency spread is compensated. Finally, the target energy is accumulated coherently via NUFFT. Compared with the random PRI generalised Radon-Fourier transform (RPRI-GRFT) and the moving target detection method for random PRI radar, the proposed algorithm achieves a good balance between the detection performance and the computational cost. Simulation results are provided to demonstrate the effectiveness of the proposed method.

A Coherent Integration Method via Radon-NUFrFT for Random PRI Radar

To deal with the problems of range cell migration (RCM) and spectrum spread during the integration time induced by the motion of a target, this paper proposes a new coherent integration method based on Radon nonuniform fractional Fourier transform (NUFrFT) for random pulse repetition interval radar. In this method, RCM is eliminated via searching in the motion parameter space and the spectrum spread is resolved by NUFrFT along the searching trajectory. Simulation results demonstrate the effectiveness of the proposed algorithm.

Aliasing-free high resolution imaging of fast rotating targets with narrowband radar

Narrowband radar has been successfully used for high resolution imaging of fast rotating targets by exploiting their micro-motion features. In some practical situations, however, the target image may suffer from aliasing due to the fixed pulse repetition interval (PRI) of traditional radar scheme. In this work, the random PRI signal associated with compressed sensing (CS) theory was introduced for aliasing reduction to obtain high resolution images of fast rotating targets. To circumvent the large-scale dictionary and high computational complexity problem arising from direct application of CS theory, the low resolution image was firstly generated by applying a modified generalized Radon transform on the time-frequency domain, and then the dictionary was scaled down by random undersampling as well as the atoms extraction according to those strong scattering areas of the low resolution image. The scale-down-dictionary CS (SDD-CS) processing scheme was detailed and simulation results show that the SDD-CS scheme for narrowband radar can achieve preferable images with no aliasing as well as acceptable computational cost.

Aliasing‐free micro‐Doppler analysis based on short‐time compressed sensing

Time–frequency distribution (TFD) has been widely used for micro-Doppler analysis in radar signal processing. However, the spectrogram will suffer from aliasing if the maximum Doppler frequency exceeds half of the pulse repetition frequency, which may lead to false estimation of the targets' kinematic properties. In this study, by transmitting a series of random pulse repetition interval (RPRI) pulses, a concise TFD approach named short-time compressed sensing (STCS) is proposed for aliasing-free micro-Doppler analysis. In STCS, precise analysis and synthesis of the random sampling time series can be achieved by exploiting the signal's sparsity in the frequency domain. Furthermore, adaptive to the data, the widths of the particular rectangle windows are determined by sequential processing with a proper optimisation rule. To speed up the STCS procedure, the smoothed L0 algorithm is chosen for sparse recovery, where the pseudoinverse of the dictionaries can be calculated iteratively. The simulation results indicate that the proposed STCS approach can achieve both preferable TFD and acceptable computational cost. The effectiveness of the STCS is finally verified by the application for micro-Doppler estimating in RPRI radar.

Aliasing-Free Moving Target Detection in Random Pulse Repetition Interval Radar Based on Compressed Sensing

The electronic counter-countermeasures capabilities of staggered pulse repetition interval (PRI) signal is limited by its repetitive character, and a random PRI radar is an alternative to improve the range and velocity coverage. However, the high sidelobe pedestal of the target Doppler spectrum caused by randomness prevents its development. In this paper, based on the compressed sensing theory, we present a novel framework in random PRI radar to generate the Doppler spectrum with low sidelobe for moving target detection. As a precondition, the equivalent sensing matrix is proved to satisfy the restricted isometry property by testifying its independent sub-Gaussian elements and comparing its mutual coherence as well as eigenvalues of its Gram matrices to a typical random compressed sensing matrix in a statistical sense. To cover the concerned velocity, multichannel processing is used and the iterative grid optimization algorithm is employed to eliminate the grid mismatch effect. The simulation results demonstrate that this scheme has high performance of detection and free aliasing characteristic, which can also shorten the coherent processing interval compared with traditional staggered PRI mode.

Novel Method of Unambiguous Moving Target Detection in Pulse-Doppler Radar with Random Pulse Repetition Interval

Novel Method of Unambiguous Moving Target Detection in Pulse-Doppler Radar with Random Pulse Repetition Interval

Novel Method of Unambiguous Moving Target Detection in Pulse-Doppler Radar with Random Pulse Repetition Interval

Novel Method of Unambiguous Moving Target Detection in Pulse-Doppler Radar with Random Pulse Repetition Interval

ADAPTIVE CLUTTER SUPPRESSION FOR AIRBORNE RANDOM PULSE REPETITION INTERVAL RADAR BASED ON COMPRESSED SENSING

We present an adaptive clutter suppression method for airborne random pulse repetition interval radar by using prior knowledge of clutter boundary in Doppler spectrum. In this method, by exploiting the intrinsic sparsity, compressed sensing based on iterative grid optimization (CS-IGO) is applied to directly recover the clutter spectrum with only the test range cell instead of nonhomogeneous training data from adjacent range cells. Since the sensing matrix and clutter spectrum obtained by CS-IGO are well adapted to the data, the prewhitening fllter can be efiectively obtained to cancel the mainlobe clutter. Further, the clutter residue can be suppressed by the iterative reweighted l1 minimization to enhance the target response. Simulation results show that the approach is capable of efiective suppression of clutter and precise recovery of targets' unambiguous spectrum, ofiering a high performance of output signal to clutter and noise ratio.

Analysis of the digital MTI filter with random PRI

Modulation of the radar pulse repetition interval (PRI) is a conventional technique to improve the target velocity coverage in a moving target indicator (MTI) filter. Typically, a given pattern of interpulse intervals is periodically repeated (staggered PRI). Additionally, the staggered PRI gives us some protection against PRI analysis in an electronic intelligence environment. Nevertheless, this protection is limited by the repetitive character of the PRI modulation pattern. Much greater protection can be achieved by means of a random selection of the PRI between fixed bounds.This paper presents an analysis of the digital MTI for two types of PRI random generation. In the first type, small deviations with respect to a mean PRI are randomly generated (random deviation method, RDM). In the second type, the intervals themselves are randomly selected random interval method, RIM). We derive for both cases the relationship between the velocitydependent gain factor and the probability density function (PDF) of the corresponding random variables. This allows us to predict the influence of the PDF in the expected performance. Specific design strategies that take into account practical constraints, like the maximum unambiguous range and the dwell time, are also proposed for each method.

Reduction of Eclipsing Loss in High PRF Radars

In order to reduce the eclipsing loss in high pulse-repetition frequency radars, one can use random pulse-repetition interval (PRI) waveforms. Random PRI waveforms are also desirable because they reduce the probability of intercept by unwanted listeners. On the other hand, since randomizing the PRI results in smearing the spectrum of the transmitted signal, the amount of clutter power (most seriously, main-lobe clutter) returned to the receiver will be enhanced over what it would have been had the PRI been uniform. Therefore, it is of interest to determine the exact form of the new power spectrum and further to determine the effects of that power spectrum on the radar system.