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The concept of space solar power satellite (SSPS) is an advanced system for collecting solar energy in space and transmitting it wirelessly to earth. However, due to the long service life, in-orbit damage may occur in the structural system of SSPS. Therefore, sensor placement layouts for structural health monitoring should be firstly considered in this concept. In this paper, based on genetic algorithm, an optimal sensor placement method for deployable antenna module health monitoring in SSPS is proposed. According to the characteristics of the deployable antenna module, the designs of sensor placement are listed. Furthermore, based on effective independence method and effective interval index, a combined fitness function is defined to maximize linear independence in targeted modes while simultaneously avoiding redundant information at nearby positions. In addition, by considering the reliability of sensors located at deployable mechanisms, another fitness function is constituted. Moreover, the solution process of optimal sensor placement by using genetic algorithm is clearly demonstrated. At last, a numerical example about the sensor placement layout in a deployable antenna module of SSPS is presented, which by synthetically considering all the above mentioned performances. All results can illustrate the effectiveness and feasibility of the proposed sensor placement method in SSPS. [ABSTRACT FROM AUTHOR]

This paper presents a novel strategy to simultaneously estimate the direction of arrival (DOA) of a source signal and the phase error of a partly calibrated array with arbitrary geometry. We add up the snapshot data of two different sensors, and then extract a knowledge associated with the DOA and phase errors of these two elements by using singular value decomposition. In such a manner, we can establish a series of linear equations with respect to the unknown DOA and phase error, by simply conducting the procedure on any two sensor elements. On this basis, it can be shown that the problem of jointly estimating DOA and phase error is equivalent to a least square (LS) problem with a quadratic equality constraint. To solve this LS problem (so that the DOA and phase error can be obtained), an effective convex–concave procedure is employed. Different from the conventional algorithms that are limited to specific array geometries, the proposed one is suitable for arrays with arbitrary geometries. More importantly, the devised method only requires one extra calibrated sensor, which is not necessarily adjacently located with the reference one. Several simulations are carried out in this paper and the effectiveness of the devised method can be clearly observed. [ABSTRACT FROM AUTHOR]

Space-borne synthetic aperture radar (SAR), as an all-weather observation sensor, is an important means in modern information electronic warfare. Since SAR is a broadband active radar system, radio frequency interference (RFI) in the same frequency band will affect the normal observation of the SAR system. Untangling the above problem, this research explores a quick and accurate method for detecting and segmenting RFI-contaminated images. The purpose of the current method is to quickly detect the existence of RFI and to locate it in massive SAR data. Based on deep learning, the method shown in this paper realizes the existence of RFI by determining the presence or absence of interference in the image domain and then performs pixel-level image segmentation on Sentinel-1 RFI-affected quick-look images to locate RFI. Considering the need to quickly detect RFI in massive SAR data, an improved network based on MobileNet is proposed, which replaces some inverted residual blocks in the network with ghost blocks, reducing the number of network parameters and the inference time to 6.1 ms per image. Further, this paper also proposes an improved network called the Smart Interference Segmentation Network (SISNet), which is based on U2Net and replaces the convolution of the VGG blocks in U2Net with a residual convolution and introduces attention mechanisms and a modified RFB module to improve the segmentation mIoU to 87.46% on average. Experiment results and statistical analysis based on the MID dataset and PAIS dataset show that the proposed methods can achieve quicker detection than other CNNs while ensuring a certain accuracy and can significantly improve segmentation performance under the same conditions compared to the original U2Net and other semantic segmentation networks. [ABSTRACT FROM AUTHOR]

This paper presents a new array response control algorithm named complex-coefficient weight vector orthogonal decomposition (C2-WORD), and its application to robust sidelobe control and synthesis in the presence of steering vector mismatch. The proposed C2-WORD algorithm is a modified version of the existing WORD approach. We extend WORD by allowing a complex-valued combining coefficient in C2-WORD, and then determine the optimal combining coefficient by maximizing the white noise gain. Moreover, assuming that the steering vector uncertainty is norm-bounded, we further devise a robust C2-WORD algorithm, which is able to precisely control the upper boundary response level of a sidelobe point as desired. To enhance the practicality of the proposed robust C2-WORD algorithm, we also study how to determine the upper norm boundary of steering vector uncertainty under various mismatch circumstances. By applying the robust C2-WORD algorithm iteratively, a robust sidelobe synthesis approach is developed. Contrary to the existing approaches, the devised robust C2-WORD algorithm offers an analytical expression of weight vector updating and can work starting from an arbitrarily specified weight. Simulation results are presented to validate the effectiveness and good performance of the robust C2-WORD algorithm on sidelobe control and synthesis in the presence of steering vector uncertainties. [ABSTRACT FROM AUTHOR]

This study aims to propose a static and dynamic evaluation for 160 m solar sail by comparing the results obtained using an 8 m scalable principle prototype. Based on the model updating and parameter modification theories, the finite element analysis (FEA) model of the 8 m prototype is constructed, and results are obtained to validate the effectiveness of the proposed numerical simulation method. The static deformation is compared with experimental data with errors in acceptable limits. Moreover, the numerical simulation and analysis method for wrinkle patterns are also applied based on the structural buckling theory and linear combination technology. The calculated indices of peak-valley value, half-wavelength, and wrinkle number are compared with the prototype experiment. By validating the numerical simulation approach in the 8 m prototype, the same analysis method can be directly extended in the application of the 160 m solar sail. The deformation response of the overall system and wrinkle patterns of the 160 m sail are provided. The transient dynamic responses of acceleration, displacement, and vibration amplitudes are also simulated and compared using different parameters. All the results obtained herein provide valuable suggestions and reference to large solar sail design in the future. • The simulation and analysis method for solar sail is validated by scalable prototype. • Wrinkles of sail are simulated based on buckling theory and validated by experiment. • Static deformation, stress and wrinkles are analyzed to evaluate 160 m sail concept. • Transient dynamic responses of 160 m sail with different parameters are provided. [ABSTRACT FROM AUTHOR]

Highlights • The significance and limitations of redundancy in sensor placement are investigated. • A novel redundancy elimination model considers global and local sensor distribution. • The strategy includes sub-clustering algorithm and smallest enclosing circle method. • The placement algorithm is with sub-clustering strategy, combined objective and GA. • The obtained dispersed sensor configuration can balance performance and redundancy. Abstract Considering the limitation of selecting several neighbor sensors in a local region similar to just single one, namely redundant information, a sensor placement algorithm for structural health monitoring is proposed based on sub-clustering strategy, in order to improve the performance of sensor configuration with less redundancy. According to the significance of redundancy, the proposed novel redundancy elimination model considers global and local effect to overcome the previous limitations in sensor distribution. Based on the sub-clustering strategy, the redundancy elimination model reflects the sensor configuration in each sub-clustering and overall structural field. The presented sub-clustering strategy for sensor placement includes three main procedures: sub-clustering algorithm, its check step and smallest enclosing circle method, thus the accuracy can be guaranteed. Combining the effective independence method with normalization and weighting factor, the proposed sensor placement algorithm can balance performance and redundancy by using genetic algorithm, which is more competitive to reduce the order difference between the two objectives. Finally, the effectiveness of the proposed redundancy elimination model is verified by a simple example, and another two engineering numerical examples including space solar power satellite and re-usable launch vehicle are applied to demonstrate the validity of the proposed sensor placement algorithm respectively. [ABSTRACT FROM AUTHOR]

Highlights • Limitation of the previous models and superiority of three-dimensional redundancy elimination model (3DREM) are proposed. • The proposed 3DREM for OSP can consider nearest neighbor nodes and sensor distribution. • By using weighting factor and normalization, the optimization problem is solved by genetic algorithm. • The first numerical example can be regarded as a benchmark structure to compare redundancy models in future studies. • The performance of sensor layout is improved and evaluated by five criteria. Abstract Spatial lattice structures are widely applied in engineering fields attributed to their superiorities in weight and reasonable stress. It is essential to select the best sensor placement layout for structural health monitoring and safety purposes, yet it is neither realistic nor efficient to place sensors in every location possible on the structure. To meet the strong requirements for optimal sensor placement in spatial lattice structure, this paper aims to investigate a combined objective function based on effective independence method and three dimensional redundancy elimination model to balance between optimal sensor placement performance and elimination in redundancy. To eliminate redundant information and resource waste caused by the clustered sensor distribution, the three-dimensional redundancy elimination model is constructed with the consideration of nearer nodes and overall sensor distribution ranges in three-dimensional cases. In addition, the combined function is constructed by giving the two component functions equal significance using weighting factors and normalization, and solved by genetic algorithm. Finally, the proposed method for spatial lattice structure is supported by three numerical examples including a simple lattice structure, a ground spatial truss structure and a space docking modular in space solar power satellite. [ABSTRACT FROM AUTHOR]

The traditional phased array radar is unable to distinguish mainlobe deceptive interference from the true target when they share an identical angle. To address this issue, a method is developed to suppress the interference in the joint transmit–receive–Doppler frequency domain, using secondary compensation and quadratic phase code (QPC) with the frequency diversity array multiple-input multiple-output (FDA-MIMO) radar. The QPC technique is employed by encoding the transmitted pulses in various spatial channels, which extends the degrees-of-freedom (DOFs) of the system. To distinguish and suppress the false targets behind the true target by at least one pulse, Doppler compensation is performed and Doppler filters are employed. To distinguish the fast-generated false targets, which are located in the same pulse with the true target, the spatial frequency compensation is implemented, which equivalently relocates the mainlobe interference to the sidelobes. Via the singular spectrum analysis (SSA) technique and the data-dependent beamforming, the interferences within the ambiguity region are suppressed. Simulation results verify the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This paper presents a new method to synthesize high-performance beampatterns, with the aid of linear fractional semidefinite relaxation (LFSDR) technique and a quasi-convex optimization approach. We consider two beampattern synthesis problems. The first one is how to determine the weight vector to maximize the array gain (or equivalently, to minimize the gain loss in mainlobe), under the condition that the amplitude response satisfies specific requirements. The second one is how to minimize the notch level at a given region, on the premise of a permissible gain loss in mainlobe. To these ends, two nonconvex optimization problems are first formulated and then relaxed to their quasi-convex forms, by using the LFSDR technique. To further solve the resultant problems, the bisection method, which is commonly used in quasi-convex optimization, is adopted. Suboptimal solutions to the original nonconvex problems are finally obtained through eigenvalue decomposition or randomization manipulations. The proposed method performs well in both the cases described earlier. Moreover, our method is not limited to the array configurations and/or noise environments. Representative simulations are presented to demonstrate the effectiveness of the proposed method in high-performance beampattern synthesis. [ABSTRACT FROM AUTHOR]

The problem of suppressing mainlobe deceptive jammers, which spoof radar systems by generating multiple false targets, has attracted widespread attention. To tackle this problem, in this paper, the multiple-input multiple-output (MIMO) radar system was utilized by applying a quadratic element phase code (QEPC) to the transmitted pulses of different elements. In the receiver, by utilizing the spatial frequency and Doppler frequency offset generated after decoding, the jammers were equivalently distributed in the sidelobes of the joint Doppler-transmit-receive domain and were distinguishable from the true target. Then, further spatial frequency compensation and Doppler compensation were performed to align the true target to the zero point in the transmit spatial and Doppler domains. Moreover, by designing appropriate coding coefficients, the jammers were suppressed by data-independent Doppler-transmit-receive three-dimensional beamforming. However, the beamforming performance was sensitive to angular estimation mismatches, resulting in performance degradation of jammer suppression. To this end, a center-boundary null-broadening control (CBNBC) approach was used to broaden the nulls in the equivalent beampattern by generating multiple artificial jammers with preset powers around the nulls. Thus, the false targets (FTs) with deviations were sufficiently suppressed in the broadened notches. Numerical simulations and theoretical analysis demonstrated the performance of the developed jammer suppression method. [ABSTRACT FROM AUTHOR]

Due to the advantages of wide coverage, continuous remote monitoring, and high measurement accuracy, the spaceborne multi‐channel surveillance radar has been widely used for the air moving target detection and tracking. In this paper, the minimum detection velocity (MDV) definition for the aerial target detection performance evaluation in a spaceborne multi‐channel radar system is analysed, where three kinds of MDV definitions based on empirical formula, output signal‐to‐clutter‐plus‐noise ratio (SCNR) loss criterion, and output SCNR criterion are discussed in detail based on theoretical analysis and simulation verification. The analysis results will provide valuable reference for the practical spaceborne radar system designment with the air target detection mode. [ABSTRACT FROM AUTHOR]

A strategy for sensor number determination and placement optimization for structural health monitoring is proposed based on an interval possibility model and clustering avoidance distribution index. The performance of sensor configuration with optimum sensor number and less redundant information is primarily improved by considering two types of incomplete information simultaneously, namely uncertainty and redundancy. This study regards uncertainty as a non-probabilistic interval number to avoid the deficiency caused by the insufficient statistical distribution of uncertain structural parameters. As long as the bound of uncertainty is obtained, then a strategy for the sensor number can be determined using the interval possibility model and effective independence method. A novel redundant information elimination model is defined to reduce the redundant information caused by sensor clustering configuration, which considers the near neighbor distance, sensor configuration region and sensor number synchronously. Based on these two methods to address incomplete information in the sensor configuration field, the strategy for sensor placement optimization constitutes a novel combined fitness function, which comprises the effective independence method and clustering avoidance distribution index. Using the normalization and weighting factor, the combined fitness function is made more competitive by eliminating the order difference between the two objectives. Therefore, the best sensor number is suggested and the corresponding optimum sensor locations are achieved simultaneously using the genetic algorithm and the proposed strategy for sensor number and placement. The performance of sensor configuration and redundant information with incomplete information is balanced by the proposed strategy. Finally, the effectiveness of the proposed strategy and method is verified through three engineering numerical examples. [ABSTRACT FROM AUTHOR]

This paper presents two secure transmission algorithms for millimeter-wave wireless communication, which are computationally attractive and have analytical solutions. In the proposed algorithms, we consider phased-array transmission structure and focus on phase shift keying (PSK) modulation. It is found that the traditional constellation synthesis problem can be solved with the aid of polygon construction in the complex plane. A detailed analysis is then carried out and an analytical procedure is developed to obtain a qualified phase solution. For a given synthesis task, it is derived that there exist infinite weight vector solutions under a mild condition. Based on this result, we propose the first secure transmission algorithm by varying the transmitting weight vector at symbol rate, thus resulting exact phases at the intended receiver and producing randomnesses at the undesired eavesdroppers. To improve the security without significantly degrading the symbol detection reliability for target receiver, the second secure transmission algorithm is devised by allowing a relaxed symbol region for the intended receiver. Compared to the first algorithm, the second one incorporates an additional random phase rotation operation to the transmitting weight vector and brings extra disturbance for the undesired eavesdroppers. Different from the existing works that are only feasible for the case of single-path mmWave channels, our proposed algorithms are applicable to more general multi-path channels. Moreover, all the antennas are active in the proposed algorithms and the on-off switching circuit is not needed. Simulations are presented to demonstrate the effectivenesses of the proposed algorithms under various situations. [ABSTRACT FROM AUTHOR]

This paper presents a geometric approach to fast array response adjustment with phase-only constraint. The devised algorithm can precisely and rapidly adjust the array response of a given point by only tuning the excitation phases of a preassigned weight vector. We geometrically reformulate the phase-only array response adjustment as a polygon construction problem, which can be solved by edge rotation in the complex plane. On this basis, we carry out a detailed analysis of the solution of polygon construction and specify the range of the feasible phase. To avoid the undesirable pattern distortion and obtain less pattern variations in the uncontrolled region, an effective and analytical phase determination approach is presented. The proposed algorithm provides an analytical solution and guarantees a precise phase-only adjustment without pattern distortion. In addition, our algorithm does not impose any restriction on the given weight vector and has a low computational complexity. Representative examples are presented to demonstrate the effectiveness of the proposed algorithm under various situations. [ABSTRACT FROM AUTHOR]

In this paper, we present two array response control algorithms for pattern synthesis with the aid of oblique projection. The proposed algorithms are developed on the basis of the weight vector orthogonal decomposition (WORD) approach, and both of them can control the array responses of multiple points starting from an arbitrarily given weight vector. They provide closed-form expressions and thus are computationally attractive and convenient to implement. Furthermore, for the preassigned angles to be controlled, the array responses can be adjusted flexibly and separately, and hence, the process of response control can be readily accomplished without complete recalculation, if some of the desired levels require adjustments. In addition, the second proposed algorithm modifies the first one and realizes the array response control without a beam axis shift. By successively performing the proposed algorithms to adjust the response to meet certain requirements, the array pattern can be synthesized. Extensive examples are provided to demonstrate the performances of the proposed algorithms in array response control and the effectiveness in pattern synthesis. [ABSTRACT FROM AUTHOR]

This paper presents a flexible array response control algorithm via oblique projection, abbreviated as FARCOP, and its application to array pattern synthesis. The proposed FARCOP algorithm stems from the adaptive array theory, and it can flexibly, precisely and simultaneously adjust the array response levels at multiple angles based on an arbitrarily given weight vector. Different from the existing approaches, the proposed FARCOP algorithm controls multi-point responses by linearly transferring the given weight vector, with a transformation matrix containing a set of parameters, each of which can be very easily determined by the desired response level (at the control angle). Owing to the fact that those parameters are independent of each other, the response levels at the control angles can be either individually or jointly and, therefore, flexibly adjusted. Since the parameter phases can be arbitrary, we take the beampattern into account and propose to uniquely choose the optimal parameters under the typical criterion of maximum white noise gain (WNG). Accordingly, a gradient projection (GP) algorithm is devised to achieve the optimal solution. Moreover, a closed-form solution is derived for the centro-symmetric array. In addition, the application of the FARCOP algorithm to pattern synthesis is discussed. Comparing to the state-of-the-art methods like multi-point accurate array response control (${\text {MA}}^2{\text {RC}}$), the proposed FARCOP algorithm controls the array responses more flexibly with lower computational complexity. Representative examples are presented to demonstrate the effectiveness and superiority of the FARCOP algorithm under various situations. [ABSTRACT FROM AUTHOR]

This paper presents a novel robust quasi-adaptive beamforming (RQAB) scheme against direction-of-arrival (DOA) mismatch. Unlike existing robust adaptive beamforming (RAB) methods, the proposed approach obtains the ultimate beamformer weight vector in a quiescent manner, nevertheless, it possesses the remarkable ability of interference rejection and desired signal reception. In this method, a two-step procedure is devised to design the quasi-adaptive weight vector. More specifically, the conventional sample matrix inversion (SMI) beamformer is first applied to find out all notch angles outside the region of interest (ROI) where the desired signal comes with a high probability. It is shown that these notch angles contain the DOAs of interferences. Then, a multipoint accurate array response control ( $ {\text {MA}}^2\text {RC}$ ) algorithm is utilized to synthesize a beampattern with the same sidelobe notch levels as the SMI, and nearly constant response over the ROI. Contrary to conventional approaches that are vulnerable to the contamination of the training data by the desired signal, our proposed approach exhibits outstanding performance under this common scenario. Moreover, besides the DOA mismatch, the proposed approach is also insensitive to the SNR, number of snapshots and mismatch angle. Additionally, different from many optimization-based RAB methods, the proposed RQAB approach offers an analytical expression of the beamformer weight vector and, hence, is computationally attractive. Typical simulation examples are provided to demonstrate the superiority of the RQAB scheme. [ABSTRACT FROM AUTHOR]

The detection and parameters estimation of linear frequency-modulated (LFM) signal are important for modern radar applications, but they are also challenged by the fact that echo signal is often of low signal-to-noise ratio (SNR) due to reasons of long imaging distance and/or limited transmitted power, and the target of small size and/or hidden characteristics. To enhance the SNR, in our previous work, a novel coherently integrated cubic phase function (CICPF) was recently developed for the parameters estimation of the multicomponent LFM signal. In the CICPF, the auto-terms are coherently integrated to enhance the performance in the case of low SNR and also to suppress the cross-terms and spurious peaks. In this paper, as an extension of our previous work, the theoretical performance analyses including several important properties and the fast implementation are provided. Furthermore, the asymptotic mean squared error of a CICPF-based estimator as well as the output SNR of a CICPF-based detector are theoretically derived in closed-forms. From the performance point of view, the proposed CICPF attains the Cramer-Rao bound at low input SNR. The complexity analysis also indicates that the CICPF with the nonuniform fast Fourier transform is computationally efficient without needing the interpolation operation and parameter search. Numerical studies of the CICPF confirm the theoretical analysis and demonstrate superior performance of the proposed approach compared with other state-of-the-art approaches, especially under the low-SNR condition. Finally, the proposed CICPF is applied for the ground moving target imaging in synthetic aperture radar. Results using simulated and experimental data demonstrate that it provides an effective means to obtain well-focused image for ground moving targets. [ABSTRACT FROM PUBLISHER]

In this paper, the problem of pattern synthesis with antenna arrays is addressed, and new approaches based on the recently developed accurate array response control ( \textrm A^2\textrm RC ) algorithm are presented. It is shown that the array weight vector obtained by the \textrm A^2\textrm RC algorithm to control the normalized response at a single direction in each step belongs to a specific set. Thus, an appropriate weight vector chosen from the intersection of weight vector sets corresponding to the desired responses at multiple directions is capable of simultaneously controlling those responses. This results in the so-called multipoint accurate array response control ( \textrm MA^2\textrm RC ) algorithm. Moreover, in order to avoid possible beam axis shift in pattern synthesis, a modified \textrm MA^2\textrm RC ( \textrm M^2\textrm A^2\textrm RC ) algorithm is proposed by imposing a derivative constraint on the direction of beam axis. Representative numerical examples are provided to demonstrate the effectiveness of the proposed \textrm MA^2\textrm RC and \textrm M^2\textrm A^2\textrm RC algorithms for multipoint responses control and pattern synthesis. [ABSTRACT FROM AUTHOR]

This paper presents a novel accurate array response control algorithm, abbreviated as \text A^2\text RC, and its application to array pattern synthesis. The proposed \text A^2\text RC algorithm deals with the problem of how to accurately control the array response at a given direction. Starting from the adaptive array theory, a deep analysis of the optimal weight vector is carried out. It is found that the normalized response at a given direction can be accurately adjusted to an arbitrary level, by means of making some simple modification to the initial weight vector. On this basis, all possible weight vectors, which have a specific form and can make the normalized response at the given direction equal to the prescribed value, are first figured out. Then, an effective approach to selecting the most appropriate one, which would cause the least pattern distortion, is devised. By applying the \text A^2\text RC algorithm, a new pattern synthesis approach for arbitrary arrays is developed. In this approach, the array pattern is adjusted in a point-by-point manner by successively modifying the weight vector. Contrary to the conventional approaches that assign artificial interferences in an ad hoc way, our approach is able to obtain the weight vector without iteratively determining the powers of the artificial interferences. Extensive simulation results are provided to demonstrate the performance of the \text A^2\text RC algorithm in array response control and the effectiveness of this algorithm in pattern synthesis under various situations. [ABSTRACT FROM PUBLISHER]

In synthetic aperture radar (SAR), long integration time may induce range migration and Doppler frequency migration of a received signal, which may degrade the SAR imaging performance of ground moving targets. Most of the conventional algorithms deal with the problems of range migration and Doppler frequency migration based on parameter searching. However, the exhaustive searching of target motion parameters may result in heavy computational burden. To avoid this problem, this paper proposes a new imaging method for ground moving targets without target motion parameter estimation. First, Keystone transform is applied to correct the range walk. Second, range curvature is compensated by the matched filtering function. Third, Doppler frequency migration is compensated via multiplying the data in range- and azimuth-time domains by its reversed conjugate data according to the equal interval sampling of the azimuth slow time, which avoids the searching procedure for target motion parameter estimation. Finally, the signal energy will be well accumulated in the range–Doppler domain, and thus, the moving targets can be efficiently recognized in the focused image. The major advantage of the proposed method is that it can obtain well-focused images of all targets in one processing step without target motion parameter estimation; thus, it is computationally efficient. Both simulated and real data processing results are used to validate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

In synthetic aperture radar (SAR) imaging of a ground moving target, long-time coherent integration may effectively improve the imaging quality, whereas the imaging performance may severely degrade due to the range migration and the Doppler frequency migration. In this paper, a novel motion parameter estimation method named second-order Wigner–Ville distribution (SoWVD) transform is proposed, and then, a new SAR imaging method based on the SoWVD for a ground moving target is developed. As a modified Wigner–Ville distribution method, the SoWVD method can estimate the motion parameter without the search procedure, which achieves motion parameter estimation by Fourier transform operations in the 2-D frequency plane with respect to the slow time and the delay time. In addition, it can effectively recognize the cross terms based on multiple symmetrical properties of the peaks in the 2-D frequency domain. Both simulated and real data processing results are presented to validate the proposed imaging method. [ABSTRACT FROM PUBLISHER]

This paper addresses the problem of detecting a signal in partially homogeneous and homogeneous environments. In partially homogeneous environments, i.e., both the test data and training data share the same noise covariance matrix structure up to an unknown scaling factor, a persymmetric adaptive coherence estimator (Per-ACE) detector is proposed. By exploiting the persymmetric structure of the covariance matrix, the Per-ACE can reduce training data requirements. Furthermore, the expressions for the probabilities of false alarm and detection are derived along with the distribution of the loss factor \beta. In homogeneous environments, a persymmetric adaptive matched filter (Per-AMF) detector has been presented. However, its probability of detection has not been obtained yet. Thus, we derive the expression for the probability of detection. For both the Per-ACE and Per-AMF, numerical results of these proposed expressions are confirmed with those of Monte Carlo trials. In addition, simulation results show that the proposed Per-ACE outperforms the conventional ACE in training-limited scenarios. [ABSTRACT FROM AUTHOR]