常用脉冲重复间隔估计算法

雷达信号分选是电子战系统(EW)与反辐射导弹(ARM)的关键技术,脉冲重复间隔(PRI)是信号分选与识别的一个重要参数,它决定了雷达的最大无模糊距离和最大无模糊径向速度。目前以脉冲序列的自相关函数为基础,利用脉冲到达时间(TOA)提出了多种脉冲重复间隔估计算法。本文介绍了几种常用算法的原理,讨论了各算法的缺陷,并给出了PRI变换应用于抖动PRI序列时的计算机仿真结果。最后分析了各种算法的性能与适用范围。     

Improved algorithm for estimating pulse repetition intervals

This paper presents an improved algorithm for estimating pulse repetition intervals (PRIs) of an interleaved pulse train which consists of several independent radar signals with different PRIs. The original version of this algorithm is a complex-valued autocorrelation-like integral, which leads to a kind of PRI spectrum wherein the locations of the spectral peaks indicate the PRI values. The original algorithm, however, has a serious drawback in that it is vulnerable to timing jitter (PRI jitter). We analyze the cause of this vulnerability and propose an improved algorithm using overlapped PRI bins which have shifting time origins. The improved algorithm has proven to be quite effective in obtaining the PRI spectrum for jittered pulse trains, which enables detection of mean PRIs by thresholding     

Processing throughput estimation for radar intercept receivers

Analytical expressions for the computational requirements of broad classes of radar pulse deinterleaving algorithms are developed. The analysis applies to block collection systems and is principally intended for systems with insufficient monopulse resolution to uniquely sort emitters on monopulse parameters alone. The analysis begins with triplet sequence search approaches and is confirmed by simulation. It is also shown that this approach generalizes to more complex deinterleaving schemes, including M-tuple search and time of arrival (TOA) difference histogramming. All cases exhibit the same basic functional form of quadratic dependence on the number of emitters, linear dependence on the collection time, and complex dependence on the pulse deletion (or dropping) probability     

Performance of a Square Law Pseudonoise Ranging Time-of-Arrival Estimator

The performance of a square law time-of-arrival (TOA) estimator that has been proposed for use in ASTRO-DABS, part of a possible satellite-based fourth generation air traffic control system is considered. The transmitted message consists of a pulse amplitude modulated (PAM) ranging sequence that, due to transmitter characteristics, is corrupted by an unknown frequency offset. The optimum TOA estimator, for the case of no frequency uncertainty, is first presented, together with a lower bound on the variance of the estimate generated. This is followed by the consideration of a suboptimum TOA estimator for which a high signal-to-noise ratio (SNR) performance analysis is carried out; here, the effects of frequency uncertainty are included. Next, the zero-crossing properties of the derivative of the (suboptimum) estimation statistic are presented and the results used to derive an upper bound to the TOA estimate variance that is valid for all SNR values. This latter result is significant because it displays the system threshold effect and complements performance lower bounds that may be derived via other methods. In addition, the method presented here may be applied to other optimum and suboptimum systems where a discrete set of parameters is to be estimated.     

An approach for parameter estimation of combined CPPM and LFM radar signal

In this paper, the problem of parameter estimation of the combined radar signal adopting chaotic pulse position modulation (CPPM) and linear frequency modulation (LFM), which can be widely used in electronic countermeasures, is addressed. An approach is proposed to estimate the initial frequency and chirp rate of the combined signal by exploiting the second-order cyclostationarity of the intra-pulse signal. In addition, under the condition of the equal pulse width, the pulse repetition interval (PRI) of the combined signal is predicted using the low-order Volterra adaptive filter. Simulations demonstrate that the proposed cyclic autocorrelation Hough transform (CHT) algorithm is theoretically tolerant to additive white Gaussian noise. When the value of signal noise to ratio (SNR) is less than 4 dB, it can still estimate the intra-pulse parameters well. When SNR = 3 dB, a good prediction of the PRI sequence can be achieved by the Volterra adaptive filter algorithm, even only 100 training samples.     

Prime sequences for asynchronous pulse repetition interval agileradar

We propose the use of prime sequences in pulse repetition agile radar to increase the immunity of the radar to reconnaissance and deceptive jamming. The prime sequences are mapped into state agile mapped (SAM) sequences and are used to determine the pulse repetition interval (PRI) of the radar. We show that this produces a system with low mutual interference between radars and with a low probability of ambiguous range measurement resulting in good resistance to active deceptive jamming     

Partially Adaptive STAP using the FRACTA Algorithm

A partially adaptive space-time adaptive processor (STAP) utilizing the recently developed FRACTA algorithm is presented which significantly reduces the high computational complexity and large sample support requirements of fully adaptive STAP. Multi-window post-Doppler dimensionality reduction techniques are employed to transform the data prior to application of the FRACTA algorithm. The FRACTA algorithm is a reiterative censoring (RC) and detection algorithm which has been shown to provide excellent detection performance in nonhomogeneous interference environments. Two multi-window post-Doppler dimensionality reduction techniques are considered: PRI-staggered and adjacent-bin. The partially adaptive FRACTA algorithm is applied to the KASSPER I (Knowledge-Aided Sensor Signal Processing & Expert Reasoning) challenge datacube. The pulse repetition interval (PRI)-staggered approach with D=6 filters per Doppler bin is found to provide the best detection performance, outperforming the fully adaptive case while simultaneously reducing the runtime by a factor of ten. Using this implementation, partially adaptive FRACTA detects 197 out of 268 targets with one false alarm. The clairvoyant processor (the covariance matrix for each range cell is known) detects 198 targets with one false alarm. In addition, the partially adaptive FRACTA algorithm is shown to be resilient to jamming, and performs well for reduced sample support situations. When compared with partially adaptive STAP using traditional sliding window processing (SWP), the runtime of partially adaptive FRACTA is 14 times faster, and the detection performance is significantly increased (SWP detects 46 out of 268 targets with one false alarm).     

基于短时时差序列的无源定位方法

针对脉冲辐射源定位问题,提出了一种基于短时时差(TDOA)序列的多站无源定位新方法.首先建立了TDoA序列模型,然后推导了该方法定位误差的克拉美罗下限(CRLB),并提出了一种高效的解算方法--两步定位法(TSLM):第1步利用TDOA序列线性估计出TDOA及其变化率信息,第2步基于TDOA及其变化率信息进行定位.典型...     

Passive localization by a single moving observer using TOA only with unknown SRI: Observability analysis and algorithm

Passive localization by a single moving observer using Time of Arrival (TOA) only with an unknown Signal Repetition Interval (SRI) is investigated in this paper. Observability analysis is performed first. The observability condition for uniquely determining the emitter position and SRI is derived. The conditional Cramer-Rao Lower Bound (CRLB) is also analyzed. It is found that the ambiguity of the SRI integer of the first TOA does not affect the theoretical estimation precision of the emitter position and SRI. A Reference-Fixed Differential TOA (RFDTOA)-based Iterative Maximum Likelihood Estimator (IMLE) is proposed, which only needs O(M) computational operations. Theoretical analysis and simulation results show that the Mean Square Error (MSE) of the proposed algorithm could attain the CRLB with moderate Gaussian measurement noise.     

Composite Bound on Arrival Time Estimation Errors

Time of arrival (TOA) estimation of narrowband signals is a problem of considerable practical interest in radar and sonar applications. A new technique is presented to analyze the mean square error (MSE) performance of TOA estimation schemes, based on recently developed lower bound. We obtain a complete characterization of the MSE as a function of the signal and noise parameters. The results are given in a simple closed-form analytical expression.     

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     

基于EMD-CS的脉冲星周期超快速估计

面向X射线脉冲星周期估计的压缩感知（CS）中测量矩阵尺寸大,进而导致计算量大。针对这一问题,提出了一种基于经验模态分解-压缩感知（EMD-CS）的脉冲星周期超快速估计方法。将不同畸变度的脉冲轮廓进行EMD分解,得到一系列固有模态函数（IMF）。由于IMF包含了不同时间尺度的局部特征信号,脉冲轮廓畸变度这一微弱局部特征可体现在某些IMF中。采用迭代剔除法剔除冗余的IMF,剩下的IMF构成了测量矩阵。由于IMF的数量较少,采样率大幅减少。利用EMD-CS可实现X射线脉冲星周期超快速估计。通过计算复杂度分析结果可知,采样率与计算量呈正比关系。仿真结果中表明,EMD-CS的采样率为0.25%,仅为FFT-CS的1/29,因而计算量更小。     

Principles and Simulation of JTIDS Relative Navigation

The time-synchronous operation and high accuracy time-of arrival (TOA) measurement capability of Joint Tactical Information Distribution System (JTIDS) terminals makes possible a high performance relative nagivaton (RELNAV) function through addition of only software in the terminal's computer program. The principles of operation, the basic observation equations, and the system architecture for both absolute (geographic) and relative navigation are described. Sequential passive ranging by means of the TOA measurements, in conjunction with appropriate source selection logic and a recursive (e. g., Kalman) filter mechanization are employed to determine the user's position, velocity, and time bias. The filter algorithms and error sources, the software functional flow, and some simulation results are presented.     

Adaptive canceler and pulse compressor interactions

Performance results for the sidelobe level of a compressed pulse that has been preprocessed through an adaptive canceler are obtained. The adaptive canceler is implemented using the sampled matrix inversion algorithm. Because of finite sampling, the quiescent compressed pulse sidelobe levels are degraded due to the preprocessing of the main channel input data stream (the uncompressed pulse) through an adaptive canceler. It is shown that if N is the number of input canceler channels (main and auxiliaries) and K is the number of independent samples per channel, then K/N can be significantly greater than one in order to retain sidelobes that are close to the original quiescent sidelobe level (with no adaptive canceler). Also it is shown that the maximum level of degradation is independent of whether pulse compression occurs before or after the adaptive canceler if the uncompressed pulse is completely contained within the K samples that are used to calculate the canceler weights. This same analysis can be used to predict the canceler noise power level that is induced by having the desired signal present in the canceler weight calculation     

Fast converging adaptive processor or a structured covariance matrix

The use of adaptive linear techniques to solve signal processing problems is needed particularly when the interference environment external to the signal processor (such as for a radar or communication system) is not known a priori. Due to this lack of knowledge of an external environment, adaptive techniques require a certain amount of data to cancel the external interference. The number of statistically independent samples per input sensor required so that the performance of the adaptive processor is close (nominally within 3 dB) to the optimum is called the convergence measure of effectiveness (MOE) of the processor. The minimization of the convergence MOE is important since in many environments the external interference changes rapidly with time. Although there are heuristic techniques in the literature that provide fast convergence for particular problems, there is currently not a general solution for arbitrary interference that is derived via classical theory. A maximum likelihood (ML) solution (under the assumption that the input interference is Gaussian) is derived here for a structured covariance matrix that has the form of the identity matrix plus an unknown positive semi-definite Hermitian (PSDH) matrix. This covariance matrix form is often valid in realistic interference scenarios for radar and communication systems. Using this ML estimate, simulation results are given that show that the convergence is much faster than the often-used sample matrix inversion method. In addition, the ML solution for a structured covariance matrix that has the aforementioned form where the scale factor on the identity matrix is arbitrarily lower-bounded, is derived. Finally, an efficient implementation is presented.     

利用不机动单站DOA、TOA的测量实现被动定位与跟踪

 可以利用多个被动探测器或单个机动的探测器实现对运动辐射源的被动定位与跟踪。本文介绍的是一种利用非机动的单个探测器所获得的DOATOA测量值,对运动辐射源实现被动定位与跟踪的新方法。在二维平面内对运动辐射源使用这种方法,通过计算机仿真显示可以获得收敛而精确的跟踪数据。     

Algebraic two-satellite TOA/FOA position solution on an ellipsoidal Earth

A direct algebraic solution is given for estimates of the ambiguous locations of an RF emitter on the surface of an ellipsoidal Earth given time-of-arrival (TOA) and frequency-of-arrival (FOA) measurements at two satellites.     

Transient Modeling of Synchronous Machine-Transformer-SCR Bridge

A rigorous mathematical model of a synchronouschine-machine-transformer-thyristor bridge unit is presented in state-space form with coefficients that are explicit functions of standard parameters. The developed model has a minimum order for each of the various operation modes of the bridge, and its form is such that it can be readily interfaced with any type of dc network connected to the bridge. In addition, the model has the capability to consider different types of transformer winding connections. In a digital simulation, the explicit form of the state model eliminates the need of matrix inversions at each integration step. This and the use of the ?, ? reference frame result in a high computing efficiency and accuracy. As an illustration, simulation results are shown of a case study where the unit is part of a high-power pulse generating system.     

高距离分辨率的低截获概率雷达信号性能研究

首先,分析步进频率雷达信号实现高分辨率的优缺点,在此基础上设计了一种改进的步进频率信号-参差脉冲重复间隔步进频率信号;然后,分析了该信号的处理过程。与步进频率信号在高速目标下成像失真相比,参差脉冲重复间隔步进频率信号的多普勒性能有了很明显的改善。最后,分析了参差脉冲重复间隔步进频率信号的低截获概率特性。     

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