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This paper proposes a pulse compression method by using the offset quadrature amplitude modulation based orthogonal frequency division multiplexing (OQAM-OFDM) signal without inserting any cyclic prefix (CP). A modified interference approximation-based pulse compression method (MIA-based PCM) is proposed, by exploiting the demodulated real weights of the OQAM-OFDM signal, the inter-symbol and inter-subcarrier interferences to enhance the performance. The MIA-based PCM achieves approximated inter-range-cell interference (IRCI)-free pulse compression and perfect Doppler estimation, which has both the benefits of power efficiency and good Doppler tolerance. Finally, numerical simulation results are provided and discussed.

In this study, a coherent detection method is proposed to solve the problems during the coherent integration (CI) process, including the range cell migration (RCM) and Doppler spread (DS) effects which are caused by the complex motions of the maneuvering target. Particularly, this method applies the third-order keystone transform firstly, which could remove the third-order RCM induced by the jerk motion. Then target's defined velocity can be estimated by performing the frequency-shifting cross-correlation function and scaled Fourier transform. Thereafter, utilising the estimated defined velocity to construct a velocity compensation function, which could correct the first-order RCM (FRCM). Subsequently, the matched filtering process is performed to eliminate the second-order RCM and DS effects. Finally, applying the Fourier transform with respect to the slow time to realise the CI.

Long time coherent integration (LTCI) technique enhances radar detection of maneuvering weak targets. Unfortunately, range migration (RM) and Doppler frequency migration (DFM) would occur during the integration period. Existing LTCI methods are all based on the assumption that the target is of single motion model (i.e., the target's motion model is fixed) during the long integration time. However, with increasing target's maneuverability and long observation time (needed to detect weak targets), the target's motion model is often changing (i.e., target is of multiple motion models) during the integration time, which would reduce the performance of existing LTCI methods significantly. In this paper, we address the LTCI problem for detecting a maneuvering weak target with multiple motion models, where the target signal model is first established. Thereafter, the short-time generalized Radon Fourier transform (STGRFT) based LTCI algorithm is proposed. The STGRFT method could not only eliminate RM and DFM but also estimate the model-changing point (i.e., the time when target's motion model changes) and accumulate the target energy distributed in different motion stages (corresponding to different motion models). Finally, numerical and real-data experiments are carried out to demonstrate its effectiveness. The results confirm that in terms of integration gain, input–output signal-to-noise ratio performance and detection ability, STGRFT-based method is superior to the existing popular LTCI algorithms.

Considering the serious performance degradation of cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM) radar range reconstruction caused by chaotic Doppler disturbance, an inter-carrier interference (ICI) cancellation problem is investigated in the scene of multiple unknown moving targets. The ICI cancellation problem is solved by proposing a two-step subcarrier alignment method. Firstly, we construct the signal model and separate the intra-pulse and inter-pulse Doppler modulation term. Then, the two-step orthogonal alignment of the subcarrier method is put forward to against ICI by Fourier analysis on the converted signal model. Later, inter-range-and-carrier (IRCI) free range reconstruction is implemented with the assistance of the CP-OFDM pulse compression method. Finally, numerical results are provided to verify the validity of the proposed algorithm.

In this paper, considering a range gate pull-off (RGPO) jamming for self-defense jamming, an optimal multiframe RGPO jamming strategy is investigated with unknown environment model. The optimal RGPO jamming strategy problem is solved by proposing a multi-frame RGPO jamming strategy optimization method based on black-box optimization technique. Firstly, we construct a multi-frame optimization model of RGPO jamming strategy by choosing the success rate of pull-off as the objective function. Then, to improve the jamming performance, a particle swarm optimization(PSO) algorithm based on Monte Carlo prediction fitness function(MC-PSO) is proposed. Finally, numerical simulation results are provided to verify the validity of the proposed method.

In this study, a signal design algorithm for radar–communications system is investigated. An arbitrary pulse length orthogonal frequency-division multiplexing with sufficient cyclic prefix (CP-based OFDM) signal is designed as the radar–communications signal, the communication symbols are embedded by proposing an interval linear phase compression (ILPC) modulation. Firstly, the authors construct the model of CP-based OFDM signal, and analyse the impact of the communication symbols embedding. Then, to decrease the impact caused by the communication symbols embedding, the ILPC modulation is proposed. To guarantee the performances of the CP-based OFDM radar–communications signal, a time/frequency domain iterative filtering and clipping method is used. This algorithm can be used to design a CP-based OFDM signal that has a balanced performance in communications and radar. Finally, numerical results are provided to verify the validity of the proposed algorithm.

Under the circumstance of simultaneously scanning multiple regions in an environment which can change as time goes by, the authors study an optimal algorithm to solve antenna deployment problem for MIMO radar systems here. It is solved by multi-objective particle swarm optimisation algorithm (MOPSO) combining an autoregressive (AR) prediction model (MOPSO-AR). In a time period and dynamic environment, the MOPSO-AR method uses the previous optimal information to calculate the current deployment schemes before PSO optimisation starts up. It greatly reduces computational load and the error of the solutions. First, by discretising the time period into several time intervals, the problem in each time interval can be seen as a static problem. However, there may be relationship between these time intervals. Second, use the previous information and an AR model to predict temporally optimal solutions. Then, to get the exact optimal solutions, the predicted solutions and PSO method was applied to compute. Simulations show that the prediction strategy improves algorithm performance.

In this paper, considering mutual interference between radar and communication signals, the closed form performance bounds of radar-communication system are investigated. Firstly, we construct a localization estimation rate for radar application. Bounds on performance of radar-communication system are measured in terms of communication data rate for the communication and localization estimation rate for the radar. Then, we derive performance bounds of the three coexistence situations, which are divided according to the coexistence manners between radar communication band. To process the received radar-communication compound signal, we operate the successive interference cancellation (SIC) scheme. Finally, numerical results are provided to demonstrate the performances of the three coexistence situations.

This paper derives the performance of the joint radar and communication system (JRCS). Firstly, for the radar application of the JRCS, we derive the mutual information (MI) between target and received signal in additive Gaussian noise. For communication, we derive the communication data rate that the JRCS can achieve. Then, under partial coexistence between radar and communication bands, the MI and communication data rate for the JRCS are derived. In terms of the overlap between the received radar and communication signals, the successive interference cancellation (SIC) scheme is adopted. Finally, the provided numerical results demonstrate the performances for the JRCS.

In this paper, we propose a range reconstruction method based on the offset quadrature amplitude modulation based orthogonal frequency division multiplexing (OQAM-OFDM) signal without adding any cyclic prefix (CP). Firstly, we establish the system model for range reconstruction based on the OQAM-OFDM signal. Then, the detailed procedures of range reconstruction are derived by applying the interference approximation method (IAM). In this way, inter-range-cell interference (IRCI) free range reconstruction and ideally zero range sidelobes are implemented. Besides, due to the non-requirement of CP, the spectrum utilization is improved compared with the range reconstruction exploiting the CP based OFDM signal. Simulation results demonstrate that the proposed method achieves the same ideally zero range sidelobes with that obtained by the approach using the CP based OFDM signal, and outperforms the conventional range reconstruction method that exploits the linear frequency modulated signal (LFM). Additionally, it shows good parameter estimation performance in different scenarios.

A moving target may enter a radar coverage area unannounced and leave after an unspecified period, which implies that the target's entry time and departure time are unknown. In the absence of these time information, target detection and parameter estimation (DAPE) will be severely impacted. In this paper, we consider the coherent detection and parameters estimation problem for a radar moving target with unknown entry time and departure time (that is, the time when the target appears-in/leaves the radar detection field is unknown), involving across range cell (ARC) and Doppler spread (DS) effects within the observation period. A new algorithm, known as window Radon Fractional Fourier transform (WRFRFT) is proposed to detect and estimate the target's time parameters (i.e., entry time and departure time) and motion parameters (i.e., range, velocity and acceleration). The observation values of a maneuvering target are first intercepted and extracted by the window function and searching along the motion trajectory. Then these values are fractional Fourier transformed and well accumulated in the WRFRFT domain, where the DAPE of target could be accomplished thereafter. Experiments with simulated and real radar data sets prove its effectiveness., 30 pages, 10 figures

In this paper, a pulse compression method is proposed with the offset quadrature amplitude modulation based orthogonal frequency division multiplexing (OQAM-OFDM) signal. By establishing the received OQAM-OFDM signal as a linear model form and without inserting any cyclic prefix (CP), we propose a concise and easily implemented pulse compression method. The proposed method realizes the inter-range-cell interference (IRCI) free pulse compression perfectly, which improves the power efficiency, and the scope of observation will not be restrained by the number of subcarriers. Besides, the signal-to-noise ratio (SNR) after the pulse compression is derived. It is proved that the SNR gain for the proposed pulse compression method can reach the same as that of the method using the matched filter. Finally, numerical simulation results are provided and discussed.

In this paper, we consider the near field source location problem for a nonuniform sparse linear array (non-USA) in the presence of sensor gain and phase errors. We present a minimum variance based iterative self-calibration method to simultaneously estimate the gain and phase error parameters as well as the calibration sources locations including ranges and azimuthes exploiting some imprecise a-priori knowledge of calibration sources. The source locations and the gain/phase errors are obtained iteratively with known range or azimuth, and continue the procedure until they are converged. Finally, at the analysis stage, we evaluate the effectiveness of the proposed technique using some numerical simulations.

This paper considers the sparse linear array (SLA) design problem of coherent unambiguous transmit for the distributed aperture coherence-synthetic radar (DACR), accounting for the antenna size constraint and geography constraint in which elements can not be placed in a given aperture. We develop the peak sidelobe level (PSL) based cost function, which considers the sum of the PSL when the mainlobe located at all scanning angles. Then, we derive the antenna element locations by minimizing the cost function through PSO algorithm. Finally, several numerical simulations verify the effectiveness of the proposed SLA design method.

This paper considers the moving target detection (MTD) problem for polarimetric multiple-input multiple-output (MIMO) radar in the presence of Gaussian clutter. By exploiting the polarimetric information, we devise two different generalized likelihood ratio tests (GLRTs) with a generic number of polarimetric channels, according to the centralized and distributed processing schemes of MIMO radar systems, respectively. Then, we provide several numerical simulations with typical parameters, and the results illustrate that the use of multiple polarimetric channels can yield a reasonable improvement in the detection of moving target.

Our previously proposed OFDM with sufficient cyclic prefix (CP) synthetic aperture radar (SAR) imaging algorithm is inter-range-cell interference (IRCI) free and achieves ideally zero range sidelobes for range reconstruction. In this OFDM SAR imaging algorithm, the minimum required CP length is almost equal to the number of range cells in a swath, while the number of subcarriers of an OFDM signal needs to be more than the CP length. This makes the length of a transmitted OFDM sequence at least almost twice of the number of range cells in a swath and for a wide swath imaging, the transmitted OFDM pulse length becomes long, which may cause problems in some radar applications. In this paper, we propose a CP based OFDM SAR imaging with arbitrary pulse length, which has IRCI free range reconstruction and its pulse length is independent of a swath width. We then present a novel design method for our proposed arbitrary length OFDM pulses. Simulation results are presented to illustrate the performances of the OFDM pulse design and the arbitrary pulse length CP based OFDM SAR imaging., Comment: 29 pages, 10 figures, regular paper

The performance of dynamic programming (DP) based track-before-detect (TBD) algorithm is seriously affected by nonhomogeneous clutter. A novel approach which combines DP algorithm with priori information is proposed in this paper. The method of choosing the valid state transitions reasonably according to the priori information of clutter intensity is analysed. And the compensation strategy to merit function is developed. Simulations demonstrate the meaningful advantage that this improved DP algorithm ensures better target tracking performance than traditional DP process in non-homogeneous clutter. (4 pages)

This work addresses the problem of adaptive multiple-input multiple-output (MIMO) radar detector in heterogeneous clutter. We first derive the generalized likelihood ratio test (GLRT) based on the two-step design procedure. Then, considering with the Bayesian framework and the prior knowledge about the clutter, we adopt the Maximum A Posteriori (MAP) estimator to the clutter covariance matrix and extend the knowledge-aided Bayesian technique to MIMO radar detection. Finally, various simulation results and comparison with respect to other conventional technique are presented to demonstrate the effectiveness of the knowledge aided Bayesian technique, especially in presence of a small amount of secondary data. (4 pages)