In this paper, two optimal resource allocation schemes are developed for asynchronous multiple targets tracking (MTT) in heterogeneous radar networks. The key idea of heterogeneous resource ...allocation (HRA) schemes is to coordinate the heterogeneous transmit resource (transmit power, dwell time, etc.) of different types of radars to achieve a better resource utilization efficiency. We use the Bayesian Cramér-Rao lower bound (BCRLB) as a metric function to quantify the target tracking performance and build the following two HRA schemes: For a given system resource budget: (1) Minimize the total resource consumption for the given BCRLB requirements on multiple targets and (2) maximize the overall MTT accuracy. Instead of updating the state of each target recursively at different measurement arrival times, we combine multiple asynchronous measurements into a single composite measurement and use it as an input of the tracking filter for state estimation. In such a case, target tracking BCRLB no longer needs to be recursively calculated, and thus, we can formulate the HRA schemes as two convex optimization problems. We subsequently design two efficient methods to solve these problems by exploring their unique structures. Simulation results demonstrate that the HRA processes can either provide a smaller overall MTT BCRLB for given resource budgets or require fewer resources to establish the same tracking performance for multiple targets.
Beamformers employ an array of antenna elements to collect the electromagnetic wave in the spatial domain and filter the corrupted signal in the element-space or beam-space. The spatial filtering ...performance of both element-space and beam-space beamformers is jointly determined by two key factors, i.e., beamformer geometry and excitation weights. In this work, we propose a cognitive sparse beamformer, which is capable of swiftly adapting entwined beamformer geometry and excitation weights according to the environmental dynamics through a “perception–action” cycle. In the “perception” step, situational information is extracted from the collected real-time data, and the sparse beamformer is updated in the “action” step via a regularized switching network, which divides the large array into groups and one antenna or beam is replaced with other candidates in the same group in the metric of array gain (AG) during each iteration. To circumvent the prohibitive computations resulted from matrix inversion accompanying with each update, closed-form formulas are derived to quantify the AG variation, thus facilitating efficient online beamformer reconfiguration. Extensive simulations show the effectiveness of the proposed cognitive sparse beamformer design method.
This paper deals with the problem of modeling high-resolution synthetic aperture radar clutter data from different vegetated areas. We analyzed moving and stationary target recognition (MSTAR) data ...sets focusing on histograms, moments, and covariance of clutter amplitude, texture, and speckle. The most celebrated statistical models are tested on real data of grass field or wood and trees to validate the goodness of fit of the compound Gaussian model in different scenarios. The results demonstrate that for grass fields, the compound Gaussian model provides a good data fitting. This is not the case for woods images where the speckle is not more Gaussian distributed. Covariance analysis and concluding remarks complete this paper
This paper deals with the problem of estimating the directions of arrival (DOA) of multiple source signals from a single observation vector of an array data. In particular, four estimation algorithms ...based on the theory of compressed sensing (CS), i.e., the classical
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minimization (or Least Absolute Shrinkage and Selection Operator, LASSO), the fast smooth
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minimization, and the Sparse Iterative Covariance-Based Estimator, SPICE and the Iterative Adaptive Approach for Amplitude and Phase Estimation, IAA-APES algorithms, are analyzed, and their statistical properties are investigated and compared with the classical Fourier beamformer (FB) in different simulated scenarios. We show that unlike the classical FB, a CS-based beamformer (CSB) has some desirable properties typical of the adaptive algorithms (e.g., Capon and MUSIC) even in the single snapshot case. Particular attention is devoted to the super-resolution property. Theoretical arguments and simulation analysis provide evidence that a CS-based beamformer can achieve resolution beyond the classical Rayleigh limit. Finally, the theoretical findings are validated by processing a real sonar dataset.
Reinforcement learning (RL) based approaches in massive multiple input multiple output (mMIMO) arrays allow target detection in unknown environments. However, there are two main drawbacks hindering ...the practical application of these approaches: (i) poor detection performance for weak targets, and (ii) mismatch between high system overhead and single functionality. In light of this, we propose a dual-functional mMIMO (DF-mMIMO) system for multi-target detection with embedded communication in this work. First, we improve the RL based multi-target detection algorithm in both "action" and "reward" steps, by adding an omni-directional detection pulse in the action step and optimizing the reward mechanism in the reward step, so greatly improving the detection probability of weak targets in strong clutter. To achieve the dual modalities, communication information is embedded into the radar transmit waveform via complex beampattern modulation. In particular, we propose a low computational complexity two-step beamformer design method. First, the transmit waveform covariance matrix is designed via convex optimization, and then the beamforming weight matrix is determined according to closed-form formulas. Extensive simulation results demonstrate that the proposed DF-mMIMO system exhibits excellent target detection capability in a scenario where both strong and weak targets co-exist with downlink communications.
This study deals with the problem of spectrum sensing and spectrum sharing for cognitive radar operating in spectrally dense environments. The authors focus on how compressed sensing in spectrum ...sensing can allow a significant reduction in acquisition time reducing the cost for high-resolution analogue-to-digital converters. They derive an algorithm for estimating the channel parameters that characterise the behaviour of the primary user of the channel and also define a spectrum-sharing method to minimise the interference between the radar and the primary user.
This paper proposes a multi-dimensional resource management (MRM) scheme for multifunctional radar systems that aims to improve multiple target tracking accuracy under dynamic jamming environments. ...The proposed scheme constructs an optimization model to coordinate the radar's power and frequency resources. To combat dynamic jammers, we present a Reinforcement Learning based active anti-jamming Markov Decision Process model. The resulting signal to interference plus noise ratio and the Bayesian Cramer-Rao lower bound under jamming environments are calculated, and a multiple target tracking performance optimization model is built for the MRM scheme. We show that the MRM problem can be decoupled as two subproblems, one for combating dynamic jammer and the other for resource allocation. A two-step solution technique is developed to solve the resulting optimization subproblem based on decoupling analysis, and the obtained solution is proven to maximize target tracking performance. Simulation results indicate that the proposed method can evidently beat the dynamic jamming and improve the target tracking accuracy within a given power budget.
Beampattern synthesis of frequency diverse arrays (FDAs) has recently raised increased attention attributed to their range-dependent beampattern. The transmit beampattern of uniform FDA appears ...<inline-formula><tex-math notation="LaTeX">S</tex-math></inline-formula>-shaped, which implies coupling in the range-angle domain and thus causing unwanted energy leakage into the area of non-interest. In this work, we propose a joint optimization of sparse FDAs to synthesize a decoupled transmit beampattern from the perspective of spatial-frequency virtual array. Specifically, both spatial and spectral configuration of FDAs are optimized via joint antenna-frequency selection. In order to solve the resultant NP-hard combinatorial optimization problem, we propose an iterative reweighting strategy to transform the original problem into a convex optimization. Further, we proceed to synthesize a time-invariant decoupled beampattern by designing a time-varying unit frequency step. Comparative simulations are provided to manifest the superior performance of the proposed FDA in the metric of normalized peak sidelobe level (NPSLL) of transmit beampatterns.
Extracellular matrix (ECM) degradation is a critical process in tumor cell invasion and requires membrane and released proteases focalized at membrane structures called invadopodia. While ...extracellular acidification is important in driving tumor invasion, the structure/function mechanisms underlying this regulation are still unknown. Invadopodia are similar in structure and function to osteoclast podosomes responsible for bone degradation, and extracellular acidification is central to podosome action, suggesting that it could also be for invadopodial function. Here, utilizing a novel system for in situ zymography in native matrices, we show that the Na⁺/H⁺ exchanger (NHE1) and NHE1-generated extracellular acidification are localized at and necessary for invadopodial-dependent ECM degradation, thereby promoting tumor invasion. Stimulation with EGF increased both NHE1-dependent proton secretion and ECM degradation. Manipulation of the NHE1 expression by RNA interference or activity via either transport-deficient mutation or the specific inhibitor cariporide confirmed that NHE1 expression and activity are required for invadopodia-mediated ECM degradation. Taken together, our data show a concordance among NHE1 localization, the generation of a well-defined acidic extracellular pH in the nanospace surrounding invadopodia, and matrix-degrading activity at invadopodia of human malignant breast carcinoma cells, providing a structural basis for the role of NHE1 in invasion and identifying NHE1 as a strategic target for therapeutic intervention.--Busco, G., Cardone, R. A., Greco, M. R., Bellizzi, A., Colella, M., Antelmi, E., Mancini, M. T., Dell'Aquila, M. E., Casavola, V., Paradiso, A., Reshkin, S. J. NHE1 promotes invadopodial ECM proteolysis through acidification of the peri-invadopodial space.
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