Random Stepped Frequency Radar Research Articles

Coherent processing for randomized stepped‐frequency radar in multi‐target scenario

Randomized stepped-frequency (RSF) radar has the potential of realizing joint high-resolution range-Doppler estimation. However, estimating multiple targets' two-dimensional parameters at high efficiency based on RSF waveforms is still a difficult issue. In this study, a novel algorithm, which estimates multiple targets' velocities by using different frequencies pulses and then generates their high-range-resolution profiles (HRRPs), is proposed for RSF radar. In the velocities estimation, by setting a certain difference-frequency parameter, a set of signals with constant range-phase terms and changing velocity-phase terms is constructed and then used to generate a new generalized Doppler spectrum called the difference-frequency Doppler spectrum (DFDS). To suppress rising noise floors caused by sidelobes and cross-terms in the DFDS, DFDSs corresponding to different difference-frequency parameters are non-coherently integrated to obtain a so-called accumulated DFDS. From the accumulated DFDS, targets are detected and their velocities are estimated. In the HRRPs generation, a special dictionary matrix is structured by using the estimated velocities, and each target HRRP, without interference from other targets, is generated via the compressed sensing (CS) technique. The proposed algorithm avoids huge computation burden by separately performing Doppler and range process, and guarantees the performance in a multi-target scenario via the noise floors suppression and CS.

Range Sidelobe Suppression for Randomized Stepped-Frequency Chirp Radar

Randomized stepped-frequency (RSF) radar, which transmits pulses with random carrier frequencies in a coherent processing interval, has an excellent electronic counter-countermeasures performance and the ability to generate the high-range-resolution profiles (HRRPs) of target with a narrow bandwidth receiver. Due to the random nature, the choice of carrier frequencies in RSF radar is usually an undersampling of available frequencies, which make the HRRP generated by matched filtering suffer from high noise-like sidelobes. In this article, we take the sinc-envelopes formed by linear-frequency-modulation pulses as well as RSF phases into account, and propose a novel (or generalized) range sidelobe suppression filters design method for RSF chirp waveform based on convex optimization (the model is transformed into a second-order cone program). By using these filters, the target HRRP with much lower sidelobes can be obtained, and the performance can be traded with the instantaneous bandwidth of the receiver, which provides a new idea for solving the sidelobe problem in RSF radar.

Randomized Stepped Frequency Radars Exploiting Block Sparsity of Extended Targets: A Theoretical Analysis

Randomized Stepped Frequency Radar (RSFR) is very attractive for tasks under complex electromagnetic environment. Due to the synthetic high range resolution in RSRFs, a target usually occupies a series of range cells and is called an extended target. To reconstruct the range-Doppler information in a RSFR, previous studies based on sparse recovery mainly exploit the sparsity of the target scene but do not adequately address the extended-target characteristics, which exist in many practical applications. Block sparsity, which combines the sparsity and the target extension, better characterizes a priori knowledge of the target scene in a wideband RSFR. This paper studies the RSFR range-Doppler reconstruction problem using block sparse recovery. Particularly, we theoretically analyze the block coherence and spectral norm of the observation matrix in RSFR and build a bound on the parameters of the radar, under which the exact recovery of the range-Doppler information is guaranteed. Both simulation and field experiment results demonstrate the superiority of the block sparse recovery over conventional sparse recovery in RSFRs.

Adaptive Clutter Suppression in Randomized Stepped-Frequency Radar

Randomized stepped-frequency (RSF) radar, which transmits random-frequency pulses in a coherent processing interval (CPI), has an excellent electronic counter-countermeasures (ECCM) performance and the ability to synthesize wide-frequency band with a narrow bandwidth receiver. However, due to the use of different frequency pulses, RSF waveform is incompatible with the conventional moving-target-detection (MTD) technique, which makes clutter suppression a difficult problem for RSF radar and limits its application. In this article, the effect of clutter on the coherent processing for RSF radar is first analyzed. The result shows that coherent processing can improve the signal-to-clutter ratio on target Doppler channel by <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$N$</tex-math></inline-formula> (number of pulses in one CPI) times, which suppresses weak clutter scatterers to a large extent whilst strong clutter scatterers would still be left influential. Focusing on dominant clutter scatterers, the adaptive range-Doppler clutter suppression algorithm, which is based on designing clutter suppression filters with two-dimensional property to obtain the clear high-range-resolution profile of moving target in clutter environment, is then proposed for RSF radar. The proposed algorithm, which takes into account clutter Doppler extension, can be used for RSF radar coherent processing in clutter environment.

Phase Compensation and Image Autofocusing for Randomized Stepped Frequency ISAR

Randomized stepped frequency (RSF) waveforms are attractive for inverse synthetic aperture radar (ISAR) imaging due to their synthetic-bandwidth system architecture and outstanding electronic counter-countermeasure characteristics. However, the extra complexities of the RSF radar's frequency oscillator and the target echo model make phase compensation and image autofocusing more complicated. In this paper, we introduce a novel method for the phase compensation and image autofocusing of RSF-ISAR. The new method consists of the following two stages: the first is a parametric coarse compensation for target radial motion, and the second is a non-parametric fine compensation for motion residuals and radar system imperfection. Two target models, a naive target consisting of unit point scatterers and a Yak-42 target obtained from field experiments, are used for numerical analysis, which shows the effectiveness and superiority of the proposed method.

Computationally efficient range profile synthesis method based on zero-padding inverse discrete Fourier transform for random stepped frequency radar

The modulation frequencies of random stepped frequency radars are randomly distributed over the expected specific bandwidth. The characteristics of random modulation frequencies make it difficult to synthesize the high-resolution range profile fleetly. A zero-padding inverse discrete Fourier transform method is proposed to address the problem. Theoretical analysis shows that the proposed method has the same signal-to-noise ratio improvement performance as the classical methods, but relatively lower computational complexity. The experimental results validate the effectiveness and efficiency of the proposed method.

Waveform design for random stepped frequency radar to estimate object velocity

A novel method to estimate the object velocity for random stepped frequency radar by the waveform design is proposed. The method utilises a so-called ‘complementary random code’ to modulate the transmitted waveform. Theoretical analyses show that the proposed method achieves a high precision in velocity estimation, which could meet the requirements of motion compensation. Moreover, its computational complexity can be significantly reduced, compared with the classical estimation methods. Finally, the simulations validate the effectiveness of the present method.

A Novel Motion Compensation Method for Random Stepped Frequency Radar with M-sequence

The random stepped frequency radar is a new kind of synthetic wideband radar. In the research, it has been found that it possesses a thumbtack-like ambiguity function which is considered to be the ideal one. This also means that only a precise motion compensation could result in the correct high resolution range profile. In this paper, we will introduce the random stepped frequency radar coded by M-sequence firstly and briefly analyse the effect of relative motion between target and radar on the distance imaging, which is called defocusing problem. Then, a novel motion compensation method, named complementary code cancellation, will be put forward to solve this problem. Finally, the simulated experiments will demonstrate its validity and the computational analysis will show up its efficiency.

Motion Analysis and Compensation Method for Random Stepped Frequency Radar Using the Pseudorandom Code

To address the defocusing problem faced by random stepped frequency (RSF) radars, this paper presents a complementary code cancellation (CCC) method to estimate the target velocity and achieve motion compensation. The proposed CCC method is capable of eliminating the coupling effect between range profile and target velocity. In this paper, we first give a block diagram of RSF radar modulated by the M-sequence-generated pseudorandom code, and introduce the baseband sampling echo model of moving target. Then, the velocity estimation accuracy is derived to show the sensitivity of high-resolution range profile to target velocity. Subsequently, the CCC method is proposed and also investigated in the application of multi-target scenario. Performance analyses demonstrate that the proposed method can satisfy the estimation accuracy requirement and improve the signal to noise ratio by the velocity accumulation. Finally, simulations show that the method is effective and more computationally efficient than the existing popular methods.

Decoupled ISAR imaging using RSFW based on twice compressed sensing

Random stepped-frequency radar without delay-Doppler coupling can suppress the range ambiguity and become less sensitive to electronic countermeasures. Considering its inherent randomness, this paper focuses on sidelobe reduction in inverse synthetic aperture radar imaging for sparse target scenes based on the compressed sensing (CS) theory. First, precise motion compensation and a high-resolution range profile (HRRP) with a low sidelobe are simultaneously achieved by the CS scheme for each train containing fewer pulses. Then, we analyze the disadvantages of conventional cross-range compression algorithms, which cannot guarantee high-quality focusing performance because there may be some false HRRPs caused by the uncertainty of the CS theory or some other factors. Finally, the modified correlation coefficient is defined to discard a large percentage of those uncorrelated HRRPs and the cross-range resolution is achieved by using the CS theory again. The validity of this decoupled imaging algorithm is demonstrated by some simulation and experimental results, which indicate that the approach is capable of precise estimation of scattering centers and effective suppression of a high sidelobe.

Cognitive random stepped frequency radar with sparse recovery

Random stepped frequency (RSF) radar, which transmits random-frequency pulses, can suppress the range ambiguity, improve convert detection, and possess excellent electronic counter-countermeasures (ECCM) ability [1]. In this paper, we apply a sparse recovery method to estimate the range and Doppler of targets. We also propose a cognitive mechanism for RSF radar to further enhance the performance of the sparse recovery method. The carrier frequencies of transmitted pulses are adaptively designed in response to the observed circumstance. We investigate the criterion to design carrier frequencies, and efficient methods are then devised. Simulation results demonstrate that the adaptive frequency-design mechanism significantly improves the performance of target reconstruction in comparison with the nonadaptive mechanism.