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This letter presents a theoretical comparative study of the performance bounds for point and extended target tracking. As a result of the additional information provided by the high-resolution sensors, the posterior Cramer–Rao lower bound (PCRLB) of the kinematic target states is proven to be always smaller under the extended target tracking framework than the point target model. Three assumptions about the two kinds of target models, which are satisfied in most target tracking problems, are presented as a sufficient condition of the inequality. This comparison result suggests the use of the extended target model to potentially achieve better performance in tracking applications. The superior performance bound is also illustrated with an elliptically modeled extended target tracking example. [ABSTRACT FROM PUBLISHER]

A new airborne MTI scheme that applies to non-homogeneous clutter environment is presented. Results of simulation have proved that the scheme has a superior ground clutter suppression performance and can effectively prevent the whitening of a target [ABSTRACT FROM PUBLISHER]

Abstract: Using the centro-symmetry property of uniform linear array (ULA), we propose an algorithm that combines the weighted minimization with the unitary transformation to improve the performance of DOA estimation. Exploiting the result of the unitary transformation, more credible weights can be obtained and the jointly sparse constraint can be further enhanced. Moreover, the unitary transformation incorporates the forward–backward spatial smoothing, which improves the performance of the weighted minimization for correlated sources. Simulations demonstrate that the proposed method can achieve better performance in terms of resolution and estimation accuracy. [Copyright &y& Elsevier]

Abstract: Space–time adaptive processing (STAP) is a well-known technique in detecting slow-moving targets in the clutter-spreading environment. When considering the STAP system with conformal radar array (CFA), the training data are range-dependent, which results in poor detection performance of traditional statistical-based algorithms. Current registration-based compensation (RBC) is implemented based on a sub-snapshot spectrum using temporal smoothing. In this case, the estimation accuracy of the configuration parameters and the clutter power distribution is limited. In this paper, the technique of sparse representation is introduced into the spectral estimation, and a new compensation method is proposed, namely RBC with sparse representation (SR-RBC). This method first establishes the relationship between the clutter covariance matrix (CCM) and the clutter spectral distribution. Based on this, it avoids the problem of lacking stationary training data and converts the CCM estimation into the solving of the underdetermined equation only with the test cell. Then sparse representation method, like iterative reweighted least square (IRLS) is used to guide the solution of the underdetermined equation towards the actual clutter distribution. Finally, the transform matrix is designed using the CCM estimation so that the processed training data behaves nearly stationary with the test cell. Because the configuration parameters and the clutter spectral response are obtained with full-snapshot using sparse representation, SR-RBC provides more accurate clutter spectral estimation, and the transformed training data are more stationary so that better signal-clutter-ratio (SCR) improvement is achieved. [Copyright &y& Elsevier]

Abstract: In the field of space–time adaptive processing (STAP), direct data domain (D3) methods avoid non-stationary training data and can effectively suppress the clutter within the test cell. However, this benefit comes at the cost of a reduced system degree of freedom (DOF), which results in performance loss. In this paper, by exploiting the intrinsic sparsity of the spectral distribution, a new direct data domain approach using sparse representation (D3SR) is proposed, which seeks to estimate the high-resolution space–time spectrum only with the test cell. The simulation of both side-looking and non-side-looking cases has illustrated the effectiveness of the D3SR spectrum estimation using focal underdetermined system solution (FOCUSS) and L1 norm minimization. Then the clutter covariance matrix (CCM) and the corresponding adaptive filter can be effectively obtained. D3SR maintains the full system DOF so that it can achieve better performance of output signal-clutter-ratio (SCR) and minimum detectable velocity (MDV) than current D3 methods, e.g., direct data domain least squares (D3LS). Therefore D3SR can deal with the non-stationary clutter scenario more effectively, where both the discrete interference and range-dependent clutter exists. [Copyright &y& Elsevier]

Abstract: The main function of Electronic Support Measure (ESM) is to receive, measure and deinterleave pulses, and then identify alternative threat emitters. Among these processes, pulse deinterleaving is vitally important because dense electromagnetic environments could cause an ESM system to receive a seemingly random pulse stream consisting of interleaved pulse trains with high noise levels. Only when we segregate different radar pulse trains from the pulse stream can we proceed with further processing. Traditional deinterleaving algorithms have demonstrated instability in unconventional circumstances (such as agility of pulse repetition interval (PRI), large noise and jitter, missing of intercepted pulses). Based on the dynamic process of different emitters, a new Statistical Association Pulse Deinterleaving (SAPD) approach is proposed based on the Multiple Hypothesis Tracking (MHT) algorithm in Multiple Target Tracking system. Simulation results have shown that the proposed algorithm can successfully identify pulse trains with constant, jittered and staggered PRI, and provide much greater accuracy in PRI estimation and pulse classification than traditional algorithms, with the presence of large noise, frequency jitter, and many missing pulses. [Copyright &y& Elsevier]

A sparse recovery‐based space‐time adaptive processing approach for airborne array radars with array amplitude/phase error self‐calibration is proposed. The amplitude/phase error of the array is considered, and the clutter characteristic, i.e. the clutter space‐time spectrum, is estimated as a sparse recovery problem with perturbations in the basis matrix and additive measurement noise. An optimisation problem is formulated to estimate the clutter space‐time spectrum and array error parameters simultaneously. An iterative alternating descent sparse recovery algorithm to solve the problem is developed. The numerical results indicate that the algorithm can realise array error self‐calibration, and thus can obtain accurate clutter characteristic estimation for better clutter suppression. [ABSTRACT FROM AUTHOR]

• A detector for subspace distributed target in partial observation is proposed. • Clutter covariance matrix is estimated by considering both the likelihood and its low-rank property. • Proposed method exhibits superiority in the change of available data, clutter rank, and estimation accuracy of noise power. This paper deals with the problem of detecting a subspace distributed target obscured by disturbance consisting of clutter plus white noise. We focus on the partial observation scenario where some of the radar observations are missing, a phenomenon that usually caused by interference, spectrum sharing, compressed sampling, and so on. Detection strategies are established based on the Rao test. Specifically, we first derive the Rao test with the assumption that the disturbance covariance matrix under the null hypothesis is known. Then, the unknown covariance matrix in the test statistic is replaced with a suitable estimate to make the detector adaptive. At the estimation stage, two cases are considered, involving with and without disturbance only secondary data. The estimate of the disturbance covariance matrix is obtained by solving an optimization problem in the respective case that considers both the likelihood maximization and low-rank property of the clutter covariance matrix. Simulation results are presented to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Aim: Rapid response systems (RRS) are present in many acute hospitals in western nations but are not widely adopted in Asia. The influence of healthcare culture and the effect of implementing an RRS over time are infrequently reported. We describe the introduction a RRS into a Singaporean hospital and the barriers encountered. The efferent limb activation rates, cardiac arrest rates and unplanned intensive care unit (ICU) admissions are trended over eleven years., Methods: We conducted a retrospective observational study using prospectively collected data derived from administrative and Medical Emergency Team (MET) databases., Results: The RRS used a MET with a single parameter track and trigger and physician led efferent limb. Barriers encountered included clinical leadership buy-in, assembling and equipping the efferent team, maintaining a non-punitive mindset, improving accessibility to MET and communicating the impact of the MET. Over an 11-year period with 488,252 hospital admissions, MET activation rates increased from 1.6/1000 admissions (2009) to 14.1/1000 admissions (2019). Code blue activations and unplanned ICU admission rates decreased from 2.9 to 1.7 and from 8.8 to 2.0/1000 admissions, respectively over the 11 years. There were associations between increasing MET activation rate and reduction in code blue activations (p = 0.013) and unplanned medical ICU admission rates (p = 0.001)., Conclusion: Implementing, sustaining and continued improvement of an RRS in Singapore is possible despite challenges encountered. With increasing activation rates over a decade, there were reductions in cardiac arrest rates and unplanned medical ICU admissions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

Background: Hepatocellular carcinoma (HCC) is a serious malignant disease with high incidence, high mortality and poor prognosis. This study aimed to establish a novel signature based on apoptosis-related genes (ARGs) to predict the prognosis of HCC., Methods: Expression data of HCC from TCGA database and the list of 160 ARGs from MSigDB were downloaded. The genes included in apoptosis-related signature were selected by univariate Cox regression analysis and lasso Cox regression analysis. Subsequently, a prognostic risk model for scoring patients was developed, and then separates patients into two groups. Kaplan-Meier and receiver operating characteristic analysis were performed to evaluate the prognostic value of the model in TCGA, GEO and ICGC databases. The characteristics of immune cell infiltration between two groups of HCC were investigated. Finally, a nomogram was plotted to visualize the prognosis prediction., Results: Nine genes (CDC25B, DAP3, ETF1, GSR, LGALS3, MGMT, PPP2R5B, SQSTM1 and VDAC2) were included in the prognostic risk model. Survival was lower in the high-risk group. Surprisingly, the high-risk group was significantly more in immune cell infiltration and with higher immunoscore and stromalscore than in the low-risk group. In addition, the risk score was an independent prognostic factor for HCC., Conclusions: Prognostic signature comprising nine ARGs could be used as a potential prognostic factor for HCC. It also provides an important idea for further understanding the immunotherapy of HCC., (© 2022. The Author(s).)

Landfill leachate is a highly contaminated and complex organic wastewater. It can be categorized into young (YL) and mature leachate (ML) based on the landfill age, with significant differences in the composition of organic matter, resulting from the significant differences in humification degree. To compare the organic composition of YL and ML, ESI FT-ICR MS was applied to systematically investigate their molecular composition, chemical properties, and structural characteristics. The molecular weight of YL organics was lower than that of ML organics. In addition, O/C and H/C distributions of YL and ML organics were significantly different. YL mainly consisted of CHO compounds and aliphatic compounds. ML mainly consisted of CHON compounds and high oxygen highly unsaturated and phenolic compounds. The unsaturation degree of YL organics was expressed by carbon double bond equivalents ((DBE-C)/C = -0.0336) and was not significantly different from that of ML (-0.0241), but nominal oxidation state of carbon (NOSC = -0.8010) and aromaticity (AI mod  = 0.1254) of YL were significantly lower than of ML (NOSC = -0.0692; AI mod  = 0.2464). In addition, YL and ML organics were rich in functional groups, but the YL organics contained more straight-chain structures. The ML organics contained fewer straight-chain structures, a larger number of benzene-ring structures, and more oxygen-containing functional groups. The more complex structural properties of ML organics may be the result of the transformation of YL organics after a long series of reactions, including electrocyclization, decarboxylation, and hydrogen abstraction reactions, which eventually increased the humification degree of leachate organic matter., (Copyright © 2021. Published by Elsevier Ltd.)

This paper considers the problem of direction-of-arrival (DOA) estimation of coherent signals on passive coprime arrays, where we resort to the fourth-order cumulants of the received signal to explore more information. A fourth-order cumulant matrix (FCM) is introduced for the coprime array. The special structure of the FCM is combined with the array configuration to resolve the coherent signals. Since each sparse array of a coprime array is uniform, a series of overlapping identical subarrays can be extracted. Using this property, we propose a generalized spatial smoothing scheme applied to the FCM. From the smoothed FCM, the DOAs of both the coherent and independent signals can be successfully estimated on the pseudo-spectrum generated by the fourth-order MUSIC algorithm. To overcome the problem of occasional false peaks appearing on the pseudo-spectrum, we use a supplementary sparse array whose inter-sensor spacing is coprime to that of either existing sparse array. From the combined spectrum aided by the supplementary sensors, the false peaks are removed while the true peaks remain. The effectiveness of the proposed methods is demonstrated by simulation examples.

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds.

Thirty surface sediments, corresponding overlying water and porewater samples were collected for analysis of organochlorine pesticides (OCPs) from Taihu Lake, China in May 2010. Altogether six OCPs, i.e. hexachlorobenzene (HCB), β-hexachlorohexane (β-HCH), p,p'-DDE, p,p'-DDD, p,p'-DDT, and o,p'-DDT were detected, and the total OCPs varied from 7.84 to 32.23 ng g(-1) in sediments, from 136.97 to 2,185.14 ng L(-1) in porewater and from 24.27 to 154.07 ng L(-1) in overlying water, respectively. The highest levels of contamination in sediment was observed in southeast of the lake, while in water and porewater samples highest levels were found in Zhushan Bay, the seriously polluted area in the north part of Taihu Lake. The partition coefficient of measured OCPs between sediment-overlying water was five and six fold higher than that between sediment-porewater, indicating the different distribution patterns of OCPs among sediment, overlying water and porewater matrices. The ratios of DDT/(DDD + DDE) ranged from 0.57 to 2.28 in sediments, 0.93-13.02 in porewater and 0.84-15.98 in overlying water, respectively, suggesting the potential new source of DDTs into the lake. The ratios of o,p'-DDT/p,p'-DDT in the three matrices were centered around 0.2-0.3, indicating the o,p'-DDT in the lake was originated from historical usage of technical DDTs.