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It is often difficult to obtain sufficient training data for adaptive signal detection, which is required to calculate the unknown noise covariance matrix. Additionally, interference is frequently present, which complicates the detecting issue. We provide a two-step method, termed interference cancellation before detection (ICBD), to address the issue of signal detection in the unknown Gaussian noise and subspace interference. The first involves projecting the test and training data to the interference-orthogonal subspace in order to suppress the interference. Utilizing traditional adaptive detector design ideas is the next stage. Due to the smaller dimension of the projected data, the ICBD-based detectors can function with little training data. The ICBD has two additional benefits over traditional detectors. Lower computational burden and proper operation with interference being in the training data are two additional benefits of ICBD-based detectors over conventional ones. We also give the statistical properties of the ICBD-based detectors and demonstrate their equivalence with the traditional ones in the special case of a large amount of training data containing no interference, This manuscript is submitted to IEEE SPL with paper ID SPL-35580-2023 and the decision "AQ - Publish In Minor, Required Changes"

Considering the atomic spatial degrees of freedom, we investigate the Bell-nonlocality dynamics of two macroscopic fields interacting with a resonant two-level atom respectively. We show that the movement of the atomic center of mass can suppress the collapse and revival of the Bell-nonlocality of the fields, and the influence is relevant with the width of the atomic wave packets. The Bell-nonlocality can disappear in a finite time for larger width of the atomic wave packets.

The Radon–Fourier transform (RFT) with a long coherent integration time has recently been proposed for detecting a moving target with an across range cell (ARC) effect. However, without effective clutter suppression, clutter will also be integrated via the RFT, which may affect weak target detection. Based on the maximal signal-to-clutter-plus-noise ratio (SCNR) criteria, a novel adaptive RFT (ARFT) is proposed in this paper to effectively detect a “low-observable” target in a clutter background. The proposed ARFT can combine RFT and adaptive clutter suppression by introducing an optimal filter weight, which is determined from the clutter's covariance matrix as well as a steering vector for a moving target with the ARC effect. In the transformed range-velocity space, the proposed ARFT can suppress background clutter and optimally integrate the target's energy. Nevertheless, with the increase in the integration time, the ARFT needs to address two difficulties in its real implementation. One is the lack of independently and identically distributed (i.i.d.) training samples in a heterogeneous clutter background, and the other is that the computational complexity is too high due to the large number of pulse samples. Therefore, a subaperture ARFT (SA-ARFT) is further proposed in this paper. It divides all coherent pulse samples into several subapertures and accomplishes adaptive clutter suppression in each subaperture. Subsequently, SA-ARFT implements coherent integration among the outputs of different subapertures. The proposed SA-ARFT method can obtain a similar SCNR improvement factor (SCNR IF) with a large number of i.i.d. training samples, while it can obtain a much higher SCNR IF than the ARFT with limited i.i.d. training samples and much lower computational complexity in a heterogeneous clutter background. Finally, some numerical results are provided to demonstrate the effectiveness of the two proposed methods.

This study focuses on estimation of clutter degrees of freedom (DOFs) for airborne multiple-input multiple-output (MIMO)-phased array radar. Firstly, two equivalent clutter models are presented, according to the transmitting subarray beampattern and synthetic-phased centre, and based on the basic steering vector. Secondly, a convenient estimating rule of clutter DOFs for airborne MIMO-phased array radar under arbitrary transmitting subarray structures is presented and proofed strictly. Finally, the simulated results indicate that airborne MIMO-phased array radar is effective both in spatial selectivity and clutter suppression, and the clutter DOFs under arbitrary transmitted subarray structures can be estimated by the proposed rule exactly. The proposed models and rule are suitable for both conventional-phased array radar and airborne MIMO radar with uniform or non-uniform transmitting subarray and sparse array, and they are valuable for the improvement of space-time adaptive processing algorithm performance.

For along-track multichannel synthetic aperture radar, this paper proposes a novel ground moving target signal model in the high-resolution complex image domain. Based on the range-Doppler imaging of static scene, the 2-D complex response of an isolated rectilinearly moving target is derived via the stationary phase principle (SPP) approximations. It is shown that moving targets in complex domain can be divided into three types according to the 2-D motion distribution and the SPP approximation conditions. Different from the known peaklike response of a static target, different amplitude and phase modulations will appear for different types of moving targets. Moreover, a single target can be split into two targets in the image when its Doppler spectrum spreads over two ambiguous Doppler zones. All types of targets will have the same Doppler interferometric effect along multichannel images, which is decided by the target's ambiguous Doppler frequency. Furthermore, with the proposed signal model, the complex image properties can be completely described and analyzed. Finally, some numerical experiments are also provided to demonstrate the effectiveness of the proposed signal model and analysis.

Based on a parametric model and some optimum methods, it has been previously proved that parametric velocity synthetic aperture radar (VSAR) may improve the performances of moving target detection and parameter estimation simultaneously. In this paper, multilook processing is studied for parametric VSAR. At first, statistical signal models are established for azimuth multilook processing (AMLP) and range multilook processing (RMLP), respectively. By combining the multiple AMLP sublook pixel vectors, it is shown that the clutter parameter estimation accuracy can be further improved via the maximum-likelihood estimation methods. Meanwhile, based on the adaptive implementation for the optimum processing of VSAR, RMLP can be used to improve slowly moving target detection performance via the noncoherent integration of multiple range sublooks. Furthermore, it is shown that the Doppler frequencies of moving targets vary linearly with different range sublooks due to the different carrier frequencies of sublooks. Therefore, based on a proposed novel two-step multilook diversity (TS-MLD) estimator for RMLP, the "azimuth location ambiguity" of VSAR can be well resolved via least squares linear regression, without configuration change of the conventional VSAR. Also, the estimation accuracy of target's unambiguous Doppler frequency, as well as target's azimuth location, is derived for the proposed TS-MLD method. Finally, numerical experiments and scene simulations are provided to demonstrate the effectiveness of the proposed multilook-based methods.

Velocity synthetic aperture radar (VSAR) is equipped with a linear array to receive the echoes from a radar illuminating area via multiple channels, each of which can reconstruct a reflectivity image for the same stationary scene. Based on analysis of pixel vector sampled among multi-images, VSAR may effectively suppress the strong ground clutter and improve moving target detection and location. In this paper, different Doppler-distributed properties are derived for the moving target and clutter, respectively. Then, we propose a novel parametric statistical model for VSAR by dividing the pixel vector into three components, namely, target, clutter, and noise. Furthermore, a method of adaptive implementation of optimal processing (AIOP-VSAR) is presented for moving target detection. It is shown that the optimum detection performance may be obtained via AIOP-VSAR, particularly for the slowly moving target in an inhomogeneous clutter environment. Also, the Cramer-Rao bounds (CRBs) are derived for the estimation of unknown model parameters, as well as the azimuth locations of moving targets, and the maximum-likelihood methods are proposed to reach these CRBs. Based on the proposed target detection and parameter estimation methods, we present a complete parametric flowchart for VSAR. It is demonstrated that the proposed flowchart may effectively mitigate the "azimuth location ambiguity" of VSAR and has the super-resolution ability to resolve "velocity layover" for multiple targets. Finally, some detailed numerical experiments and scene simulations are provided to show the effectiveness of the proposed methods.

We employ all-electron full-potential linearized muffin-tin orbital method (FP-LMTO) within the frame of density functional theory (DFT) to calculate the equilibrium lattice parameters, five independent elastic constants and Debye temperature of LiBC. The equilibrium lattice parameters obtained are in good agreement with experimental data and those by others. The Debye temperature OD from the calculated elastic constants of LiBC is higher than that of MgB(2) and TiB(2). The anisotropies of the three types of elastic waves in LiBC at zero pressure have been discussed. It is found that the anisotropy of compressional waves in LiBC is considerably larger than that in MgB(2) and TiB(2). (c) 2006 Elsevier B.V. All rights reserved.

Space-time adaptive processing (STAP) holds tremendous potential for the new generation airborne surveillance radar, in which the phased array antennas and pulse Doppler processing mode are adopted. A new STAP approach using the multiple-beam and multiple Doppler channels is presented here for airborne phased array radar. The approach with space-time multiple-beam (STMB) architecture is robust to array errors and has very low system degrees of freedom (DOFs). Hence, it has low sample support requirement and it is very suitable for the practical planar phased array radar under nonhomogeneous clutter environments. Meanwhile, a new nonhomogeneous detector (NHD) based on the correlation dimension (CD) is also proposed here, which is used as an effective method to screen tracing data prior to detection processing. It can further improve the performance of the STAP approach in the severely nonhomogeneous clutter environments. Therefore, a scheme that incorporates the correlation dimension nonhomogeneity detector (CD-NHD) with the STMB is recommended, which we term CD-NHD-STMB. The experimental simulation results indicate that: 1) the STMB processor is robust to array element error and has high performance under nonhomogeneous clutter environments; 2) the CD-NHD is also effective on the nonhomogeneous clutter. As a result, the CD-NHD-STMB scheme is robust to array element error and nonhomogeneous clutter, and therefore available for airborne phased array radar applications.

Space-time adaptive processing (STAP) has been widely discussed for airborne radar systems to improve the system performance of detecting targets. This is especially true for airborne early warning (AEW) radar, which should find long-range and small radar cross section (RCS) targets such as the stealth aircraft and missiles. However, in existing airborne radar literature, STAP is mainly considered for clutter and jamming rejection in side-looking airborne radar (SLAR) applications. There have been fewer discussions on airborne radar with non-side-ways looking array radar (non-SLAR). The STAP of non-SLAR such as forward looking array radar is also very important and can not be avoided for airborne radar to detect targets in all directions. The STAP of the non-SLAR is studied here. A scheme has been proposed, which is processed by the way of STAP combined with multiple staggered medium pulse repetition frequencies (PRFs). We further study the selection of PRFs in order to make the scheme more available for non-SLAR radar. We analyze two typical non-SLAR cases, i.e., inclined-sideways looking array and forward looking array. We examine this scheme by comparing the performances of three processing systems under the criteria of range-velocity blind zone minimization. Computer simulation results show the multiple-PRFs STAP scheme is feasible for non-SLAR and can be applied to phased-array AEW radar systems.