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Electrogenic vortex wave refer to the wave that carry orbital angular momentum (OAM) in the radio frequency (RF) domain. The OAM mode is expected to be initially explored and applied as a full novel spatial dimension resource. However, the radiation energy distribution pattern of electromagnetic vortex wave exhibits a central hollow. The energy hollow phenomenon has become one of the major drawbacks limiting the popularization of electromagnetic vortex wave. In this article, a generation scheme of convergent vortex wave is proposed and research generated by uniform circular array (UCA). Orthogonal waveforms are introduced into the antenna to change the phase relationship between the original signals so that the energy remains in the wave center region. The numerical results validate the effectiveness of the proposed scheme. The circular intensity disappears, while the spiral phase wavefront features can still be maintained.

This study deals with orthogonal waveform design for multi-input multi-output (MIMO) radar. Chaos is introduced to generate orthogonal phase-coded waveforms of arbitrary coded length for arbitrary number of transmitters. However, most of these chaos-based waveforms suffer high range sidelobe level and intrapulse Doppler intolerance for pulse compression. A complementary transmitting structure is proposed for the MIMO radar to supress these high range sidelobes, and an adaptive clonal selection algorithm is introduced to search for the optimal complementary codes of the transmitted chaotic phase-coded waveform. This algorithm proves that it is convergent in theory as well. A multiple hypotheses approach is introduced at the transmitters to estimate and then compensate for the intrapulse Doppler phase shift for MIMO radar pulse compression countering the intrapulse Doppler intolerance. Numerical simulations with four typical chaotic maps are carried out and compared with Deng's codes, which validate the proposed methods of this study.

Aiming at maximizing waveform diversity gain when designing a phase-coded multiple-input multiple-output (MIMO) radar waveform set, it is desirable that all waveforms are orthogonal to each other. Hence, the lowest possible peak cross-correlation ratio (PCCR) is expected. Meanwhile, low peak auto-correlation side-lobe ratio (PASR) is needed for good detection performance. However, it is difficult to obtain a closed form solution to the waveform set from the expected values of the PASR and PCCR. In this paper, the waveform set design problem is modeled as a multi-objective, NP-hard constrained optimization problem. Unlike conventional approaches that design the waveform set through optimizing a weighted sum objective function, the proposed optimization model evaluates the performance of multi-objective functions based on Pareto level and obtains a set of Pareto non-dominated solutions. That means that the MIMO radar system can trade off each objective function for different requirements. To solve this problem, this paper presents a multi-objective quantum genetic algorithm (MoQGA) based on the framework of quantum genetic algorithm. A new population update strategy for the MoQGA is designed based on the proposed model. Compared to the state-of-the-art methods, like BiST and Multi-CAN, the PASR and PCCR metrics of the waveform set are 0.95–3.91 dB lower with the parameters of the numerical simulation. The MoQGA is able to minimize PASR and PCCR of the MIMO radar waveform set simultaneously.

Interrupted-sampling repeater jamming (ISRJ) is a kind of intra-pulse coherent deception jamming that can generate false target peaks in the range profile and interfere with the detection and tracking of real targets. In this paper, an anti-ISRJ method based on the intra-pulse orthogonal waveform is proposed, which can recognize common interference signals by comparing sub-signal matched filtering results. For some special scenes where real targets cannot be directly differentiated from false targets, a new recognition method based on the energy discontinuity of the interference signal in the time domain is proposed in this paper. The method proposed in this paper can recognize real and false targets in all ISRJ modes without any prior information, such as jammer parameters, with a small amount of calculation, which is suitable for actual radar systems. Simulation experiments using different interference parameters show that although this method has a 3 dB loss of pulse compression gain, it can completely suppress different kinds of ISRJ interference when the SNR before pulse compression is higher than −20 dB, with 100% target detection probability.

Waveform diversity (WD) represents a dynamic and transformative technology widely used in radar systems to enhance sensitivity and discrimination capabilities. Recently, WD techniques have been extensively explored for their potential ambiguity suppression within synthetic aperture radar (SAR) systems. Among these, the alternate transmitting mode combined with orthogonal waveforms emerges as a particularly promising solution. This study focuses on optimizing the power spectrum density (PSD) of signals to design and generate an orthogonal waveform pair that achieves both a low cross-correlation-to-autocorrelation ratio (CAR) and satisfactory imaging performance. Initially, we construct a fractional programming model with convex constraints to minimize the CAR. To address this challenge, we introduce an iterative optimization procedure for the PSD variable, which sequentially reduces the CAR. Each optimization step can be efficiently solved using a quadratically constrained quadratic program, ensuring that the resulting computational complexity remains low. Building on the optimized PSD, we established a parametric piecewise linear model to generate an orthogonal waveform pair. This model not only maintains a low CAR but achieves satisfactory imaging performance in real-time applications. Consequently, this orthogonal waveform pair effectively suppresses range ambiguity in SAR systems. Finally, we demonstrated the practicability and effectiveness of the proposed orthogonal waveforms through detailed simulation experiments, specifically targeting ambiguity suppression in conventional quad-polarization SAR systems.

Conventional multiple‐input multiple‐output orthogonal frequency division multiplexing (MIMO‐OFDM) radar systems typically adopt the equidistant subcarrier interleaving (ESI) scheme to generate orthogonal transmit (TX) waveforms in the frequency domain. However, the ESI scheme is limited by a reduced unambiguous distance and distance‐dependent angle errors. To mitigate these issues, this paper proposes a hybrid range‐ and Doppler‐division multiplexing (RDM‐DDM) scheme for MIMO‐OFDM radar, which separates TX signals in both the distance and velocity domains. We first establish the signal model for the hybrid MIMO‐OFDM radar system. At the receiver, we implement distance–velocity–angle processing using fast Fourier transforms (FFTs). Additionally, an ambiguous‐cell Doppler correction algorithm is applied to mitigate intercarrier interference (ICI) and resolve velocity ambiguity. This hybrid scheme increases the number of virtual MIMO channels, eliminates distance‐dependent angle errors, and enhances angle estimation accuracy. Furthermore, it overcomes the inherent limitations of standalone RDM or DDM, allowing for adaptive control of unambi guous distance and velocity by adjusting the hybrid ratio. Simulations based on a 77‐GHz 8 × 8 antenna array configuration validate the effectiveness and superior performance of the proposed schemes.

The orthogonality of transmitted waveforms is an important factor affecting the performance of MIMO radar systems. The orthogonal coded signal is a commonly adopted waveform in MIMO radar, and its orthogonality depends on the used orthogonal discrete code sequence set (ODCSs). Among existing optimization algorithms for ODCSs, the results designed by the greedy code search-based memetic algorithm (MA-GCS) have exhibited the best autocorrelation and cross-correlation properties observed so far. Based on MA-GCS, we propose a novel hybrid algorithm called the memetic algorithm with iterative greedy code search (MA-IGCS). Extensions involve replacing the greedy code search used in MA-GCS with a more efficient approach, iterative greedy code search. Furthermore, we propose an “individual uniqueness strategy” and incorporate it into our algorithm to preserve population diversity throughout iteration, thereby preventing premature stagnation and ensuring the continued pursuit of feasible solutions. Finally, the design results of our algorithm are compared with the MA-GCS. Experimental results demonstrate that the MA-IGCS exhibits superior search capability and generates more favorable design results than the MA-GCS.

To meet the increasing demands for remote sensing, a number of radar systems using Linear Frequency Modulation (LFM) waveforms have been deployed, causing the problem of depleting frequency resources. To address this problem, several researchers have proposed the Spectrum Shared Radar System (SSRS) in which multiple radars share the same frequency band to transmit and receive their own signals. To mitigate the interferences caused by the signal transmission by other radars, SSRS employs orthogonal waveforms that inherit the orthogonality of the waveforms from orthogonal codes. However, the inherited orthogonality of the codes is significantly reduced when incorporating LFM waveforms with the codes. To solve this problem, in this paper, we propose a novel but simple scheme for generating a set of optimized coded LFM waveforms via new optimization framework. In the optimization framework, we minimize the weighted sum of autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP) of the coded LFM waveforms to maximize the orthogonality of the waveforms. Through computer simulations, we show that the waveforms generated by the proposed scheme outperform the waveforms created by previous proposals in terms of ASP and CP.

In recent years, multi-input multi-output (MIMO) synthetic aperture radar (SAR) systems, which can promote the performance of 3D imaging, high-resolution wide-swath remote sensing, and multi-baseline interferometry, have received considerable attention. Several papers on MIMO-SAR have been published, but the research of such systems is seriously limited. This is mainly because the superposed echoes of the multiple transmitted orthogonal waveforms cannot be separated perfectly. The imperfect separation will introduce ambiguous energy and degrade SAR images dramatically. In this paper, a novel orthogonal waveform separation scheme based on echo-compression is proposed for airborne MIMO-SAR systems. Specifically, apart from the simultaneous transmissions, the transmitters are required to radiate several times alone in a synthetic aperture to sense their private inner-aperture channels. Since the channel responses at the neighboring azimuth positions are relevant, the energy of the solely radiated orthogonal waveforms in the superposed echoes will be concentrated. To this end, the echoes of the multiple transmitted orthogonal waveforms can be separated by cancelling the peaks. In addition, the cleaned echoes, along with original superposed one, can be used to reconstruct the unambiguous echoes. The proposed scheme is validated by simulations.

Simultaneously polarimetric radar (SPR) realizes the rapid measurement of a target’s polarimetric scattering matrix by transmitting orthogonal radar waveforms of good ambiguity function (AF) properties and receiving their echoes via two orthogonal polarimetric channels at the same time, e.g., horizontal (H) and vertical (V) channels (antennas) sharing the same phase center. The orthogonality of the transmitted waveforms can be realized using low-correlated phase-coded sequences in the H and V channels. However, the Doppler tolerances of the waveforms composed by such coded sequences are usually quite low, and it is hard to meet the requirement of accurate measurement regarding moving targets. In this paper, a joint design approach for unimodular orthogonal complementary sequences along with the optimal receiving filter is proposed based on the majorization–minimization (MM) method via alternate iteration for obtaining simultaneously polarimetric waveforms (SPWs) of good orthogonality and of the desired AF. During design, the objective function used for minimizing the sum of the complementary integration sidelobe level (CISL) and the complementary integration isolation level (CIIL) is constructed under the mismatch constraint of signal-to-noise ratio (SNR) loss. Different SPW examples are given to show the superior performance of our design in comparison with other designs. Finally, practical experiments implemented with different SPWs are conducted to show our advantages more realistically.