A noncoherent adaptive detection technique

An adaptive detection technique suitable for both stationary and nonstationary noise environments based upon a generalized likelihood ratio test (GLRT) formulation is presented. The detector, which is statistically equivalent to a special form of the Wilks's lambda test, noncoherently combines the information contained in a pulse train of arbitrary length for decision-making purposes. The probability density function of the test under the noise only hypothesis is shown to be central χ². Under the signal plus noise hypothesis, an exact statistical characterization of the test cannot be obtained, and, therefore, a Chernoff bound is derived. Results in terms of the probability of detection versus signal-to-noise ratio (SNR) obtained from Monte Carlo simulation, the Chernoff bound, and the optimal matched filter case are examined. The performance of the noncoherent detector is shown to be a function of the covariance matrix estimate and the number of data samples     

Optimization of multiframe target detection schemes

We optimize the performance of multiframe target detection (MFTD) schemes under extended Neyman-Pearson (NP) criteria. Beyond the per-track detection performance for a specific target path in conventional MFTD studies, we optimize the overall detection performance which is averaged over all the potential target paths. It is shown that the overall MFTD performance is limited by the mobility of a target and also that optimality of MFTD performance depends on how fully one ran exploit the information about the target dynamics. We assume a single target situation and then present systematic optimization by formulating the MFTD problems as binary composite hypotheses testing problems. The resulting optimal solutions suggest computationally efficient implementation algorithms which are similar to the Viterbi algorithm for trellis search. The optimal performances for some typical types of target dynamics are evaluated via Monte-Carlo simulation     

多守恒性的差分格式的分析和比较

球面大气浅水波方程(在忽略摩擦和外源强迫的条件下)具有总能量、总质量、总位涡、总位涡拟能和总角动量守恒等五个重要的物理守恒性.然而,将大气浅水波方程差分离散化后,常常不能保持这些守恒性.本文对新发展的两种较好的差分格式进行比较;一种可称之为修正总能量守恒格式,它可以较好地保持上述五个守恒性中的四个;而另一种可称之为准辛格式,它可以使上述五种守恒性均近似保持.文中对这两类格式作了具体分析,并作相应的数值试验和比较,结果表明这两类格式均值得推广应用.     

Adaptive detection schemes in compound-Gaussian clutter

Radar detection of coherent pulse trains embedded in compound-Gaussian disturbance with partially known statistics is discussed. We first give a thorough derivation of two recently proposed adaptive detection structures. Next, we derive a different detection scheme exploiting the assumption that the clutter is wide-sense stationary. Resorting to the theory of circulant matrices, in fact, we demonstrate that the estimation of the structure of the clutter covariance matrix can be reduced to the estimation of its eigenvalues, which in turn can be (efficiently) done via fast Fourier transform codes. After a thorough performance assessment, mostly carried on via computer simulations, the results show that the newly proposed detector achieves better performance than the two previously introduced adaptive detectors. Moreover, a sensitivity analysis shows that, even though this detector does not strictly guarantee the constant false alarm rate property with respect to the clutter covariance matrix, it is robust, in the sense that its performance is only slightly affected by variations in the clutter temporal correlation     

A novel target detection approach based on adaptive radar waveform design

To resolve problems of complicated clutter, fast-varying scenes, and low signal-clutterratio (SCR) in application of target detection on sea for space-based radar (SBR), a target detection approach based on adaptive waveform design is proposed in this paper. Firstly, complicated sea clutter is modeled as compound Gaussian process, and a target is modeled as some scatterers with Gaussian reflectivity. Secondly, every dwell duration of radar is divided into several sub-dwells. Regular linear frequency modulated pulses are transmitted at Sub-dwell 1, and the received signal at this sub-dwell is used to estimate clutter covariance matrices and pre-detection. Estimated matrices are updated at every following sub-dwell by multiple particle filtering to cope with fast-varying clutter scenes of SBR. Furthermore, waveform of every following sub-dwell is designed adaptively according to mean square optimization technique. Finally, principal component analysis and generalized likelihood ratio test is used for mitigation of colored interference and property of constant false alarm rate, respectively. Simulation results show that, considering configuration of SBR and condition of complicated clutter, 9 dB is reduced for SCR which reliable detection requires by this target detection approach. Therefore, the work in this paper can markedly improve radar detection performance for weak targets.     

两种多重网格法求解径流叶轮机械可压流动

为了加快数值求解叶轮机械内部流场的收敛速度,并改善计算结果,在数值求解径流叶轮机械可压流动的计算中,采用了由微元、二重和三重网格逐级转入和同时转入的两种多重网格法。对德国宇航局Ｋｒａｉｎ Ｈ设计的离心压气机内部流场的数值计算表明,两种多重网格法的计算结果差别不大,尽管在收敛速度方面存在差异,但均与测量数据吻合比较好。     

Multistage partially adaptive STAP CFAR detection algorithm

A new method of partially adaptive constant false-alarm rate (CFAR) detection is introduced. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The performance is evaluated using the general framework of space-time adaptive processing (STAP) for the cases of both known and unknown covariance. It is demonstrated that this new approach to partially adaptive STAP outperforms the more complex eigen-analysis approaches using both simulated DARPA Mountain Top data and true pulse-Doppler radar data collected by the MCARM radar     

Spatial adaptive subspace detection in OTH radar

The work presented here addresses the problem of target detection against spatially structured interference composed of jamming plus noise, where for practical reasons, the received target wavefront may also deviate from the traditional plane wave model. This detection problem arises in over-the-horizon (OTH) radar systems where spatially distributed targets often compete for detection against directional interference that is spread over the entire range-Doppler search space. Conventional detection processing schemes are compared with a recently proposed adaptive subspace detector (ASD) that takes both the spatial structure of the interference and the possibility of target wavefront distortions into account. Experimental array data recorded by the Jindalee sky-wave and Iluka surface-wave OTH radar systems, located in central and northern Australia respectively, is used to evaluate detection performance.     

Blind adaptive decision fusion for distributed detection

We consider the problem of decision fusion in a distributed detection system. In this system, each detector makes a binary decision based on its own observation, and then communicates its binary decision to a fusion center. The objective of the fusion center is to optimally fuse the local decisions in order to minimize the final error probability. To implement such an optimal fusion center, the performance parameters of each detector (i.e., its probabilities of false alarm and missed detection) as well as the a priori probabilities of the hypotheses must be known. However, in practical applications these statistics may be unknown or may vary with time. We develop a recursive algorithm that approximates these unknown values on-line. We then use these approximations to adapt the fusion center. Our algorithm is based on an explicit analytic relation between the unknown probabilities and the joint probabilities of the local decisions. Under the assumption that the local observations are conditionally independent, the estimates given by our algorithm are shown to be asymptotically unbiased and converge to their true values at the rate of O(1/k/sup 1/2/) in the rms error sense, where k is the number of iterations. Simulation results indicate that our algorithm is substantially more reliable than two existing (asymptotically biased) algorithms, and performs at least as well as those algorithms when they work.     

On adaptive multiband signal detection with GLR algorithm

An adaptive multiband detector based on the principle of the generalized likelihood ratio test (GLR) is presented. Its detection performance is studied and compared with that of the corresponding single-band GLR detector. The multiband detector is shown to significantly outperform the single-band under the chosen system constraint, especially when the amount of data available from a single frequency band is severely limited by the environment     

Novel single-phase AC/DC converter with two PWM control schemes

A novel single-phase AC/DC converter with two pulsewidth modulation (PWM) schemes is proposed to draw a sinusoidal line current with nearly unity power factor, achieve balanced neutral point voltage and regulate the DC bus voltage. With the aid of neutral point clamped scheme, a three-level voltage pattern is generated on the AC side of the proposed rectifier. To track the tine current command derived from a voltage controller and a phase-locked loop circuit, a hysteresis current control scheme is used in the inner loop control. A capacitor voltage compensator is employed to achieve the balanced neutral point voltage. To investigate the effectiveness of the proposed control scheme, the simulation and experimental results based on a laboratory prototype circuit are performed.     

两种空气/煤油燃气发生器富油燃烧组织方案对比

根据空气/煤油富油燃烧的特点,提出了两种空气/煤油燃气发生器富油燃烧组织方案,设计了采用钝体稳定火焰和旋流空气、二次喷注空气稳定火焰的两种燃气发生器.为了对比两种方案的点火和燃烧特性,对两种燃气发生器进行了一系列热试,结果表明余氧系数是燃气发生器最重要的工况参数.随着余氧系数的增加,燃气发生器的状态逐渐从启动失败变为中途熄火,最终呈正常启动状态.采用钝体稳定火焰的燃气发生器稳定工作的余氧系数边界为0.518,采用旋流空气和二次喷注空气稳定火焰可将该边界延伸到0.237,极大地扩大了燃气发生器的工作范围.与钝体稳定火焰的燃气发生器相比,旋流空气和二次喷注空气稳定火焰的燃气发生器的富油燃烧的燃烧效率提高了20%.两种方案结构复杂性相当,旋流空气和二次喷注空气稳定火焰的燃气发生器不需要冷却火焰稳定器,可提高燃气发生器的工作时间.      

Performance of an adaptive detection algorithm; rejection ofunwanted signals

The analysis of an adaptive detection algorithm described previously by the author (1985, 1986) is extended. Previously, the performance was evaluated for the case of a signal corresponding exactly to the steering vector used in the derivation of the algorithm. Here the performance for signals arriving from other directions is evaluated. It is shown that these signals are rejected much more strongly than would be suggested by the sidelobe levels of the adapted patterns themselves     

Covariance matrix estimation for adaptive CFAR detection incompound-Gaussian clutter

We address the estimation of the structure of the covariance matrix and its application to adaptive radar detection of coherent pulse trains in clutter-dominated disturbance modeled as a compound-Gaussian process. For estimation purposes we resort to range cells in spatial proximity with that under test and assume that these cells, free of signal components, can be clustered into groups of data with one and the same value of the texture. We prove that, plugging the proposed estimator of the structure of the covariance matrix into a previously derived detector, based upon the generalized likelihood ratio test (GLRT), leads to an adaptive detector which ensures the constant false alarm rate (CFAR) property with respect to the clutter covariance matrix as well as the statistics of the texture. Finally, we show that this adaptive receiver has an acceptable loss with respect to its nonadaptive counterpart in cases of relevant interest for radar applications     

On adaptive multiband signal detection with the SMI algorithm

In a nonstationary and/or nonhomogeneous interference environment, an adaptive system for target detection may suffer a severe performance degradation due to the lack of a sufficient amount of data from which the system can learn (estimate) the statistics of the environment. The detection performance of an adaptive system, which employs a frequency diversity (multiband) signaling waveform and a multiband sample matrix inversion algorithm (SMI), is analyzed. By comparison with the corresponding single-band system under the chosen system constraint, it is shown that the multiband system can significantly outperform the single band when the amount of data available from a single frequency band is severely limited by the environment     

两种差分格式和两种湍流模型在轴对称冲击射流数值计算中的比较

用延迟修正QUICK和乘方两种差分格式，结合标准k-ε模型和一种基于重正化群（RNG）思想的k-ε模型，对半封闭轴对称涡流冲击射流场进行了数值模拟。通过与实验结果的比较，考察了两种差分格式对计算结果的影响，并讨论了两种湍流模型对冲击射流场的数值预测能力。研究表明：当都采用标准k-ε模型时，QUICK格式得到的结果比乘方格式更接近于实验值，尤其对湍流能分布；当都采用QUICK格式时，RNG k-ε模型的预测值比标准k-ε模型更准确。     

Robust adaptive radar detection in the presence of steering vector mismatches

In this paper, we consider the problem of robust radar detection in the presence of Gaussian disturbance with unknown covariance matrix. We design and assess three new robust adaptive detectors, capable of operating in the presence of unknown discrepancies between the nominal and the actual steering vector. Remarkably the new decision rules exhibit a bounded constant false alarm rate (CFAR) behavior and allow, through the regulation of a design parameter, to trade off target sensitivity with sidelobes energy rejection. Finally, computer simulations show that the proposed detectors achieve a visible performance improvement, in many situations of practical interest, over the traditional adaptive detection algorithms, especially in the presence of severe steering vector mismatches.     

涡轮泵实时故障检测的改进自适应相关阈值算法

1引言火箭发动机在飞行使用之前,需要分析试车振动数据以评估发动机的性能与状态[1]。涡轮泵是液体火箭发动机中最复杂故障概率最高的部件[2],而振动是涡轮泵故障的重要起因[3],因此,涡轮泵振动数据的分析显得尤为重要。目前,它的主要分析方法有时域统计[4]、频谱分析[5]、神经     

二维非结构网格上的高精度有限体积WENO格式

构造了非结构网格上二维双曲型守恒律的一类新的高精度有限体积WENO格式。其主要思想是:根据格式精度的要求,按照谱体积方法对三角形单元网格进行剖分,通过选取适当的子单元组成模板,利用WENO重构方法重构二阶和三阶多项式,利用有限体积公式和高阶Runge-Kutta TVD时间离散方法,构造了非结构网格上二维双曲型守恒律的一致二阶和三阶精度的有限体积WENO格式。然后,推广到二维Euler方程组。最后,给出几个数值算例,验证了格式的稳定性、高阶精度和高分辨捕捉激波等间断的能力。