New correlated MIMO radar covariance matrix design with low side lobe levels and much lower complexity

In this paper, a new correlated covariance matrix for Multi-Input Multi-Output (MIMO) radar is proposed, which has lower SideLobe Levels (SLLs) compared to the new covariance matrix designs and the well-known multi-antenna radar designs including phased-array, MIMO radar and phased-MIMO radar schemes. It is shown that Binary Phased-Shift Keying (BPSK) waveforms that have constant envelope can be used in a closed-form to realize the proposed covariance matrix. Therefore, there is no need to deploy different types of radio amplifiers in the transmitter which will reduce the cost, considerably. The proposed design allows the same transmit power from each antenna in contrast to the phased-MIMO radar. Moreover, the proposed covariance matrix is full-rank and has the same capability as MIMO radar to identify more targets, simultaneously. Performance of the proposed transmit covariance matrix including receive beampattern and output Signal-to-Interference plus Noise Ratio (SINR) is simulated, which validates analytical results.     

Design of Optimal Radar Signals Subject to a Fixed Amplitude Constraint

The problem of designing finite-pulse-train radar signals and receivers to maximize the detectability of targets masked by thermal noise and clutter returns is considered in this paper. A practical constraint is introduced: the amplitude of each subpulse in the transmit waveform is taken to be fixed. The need for such a constraint is dictated in most radar applications, because the transmitter is most efficiently utilized by saturating its amplifying tube. An algorithm for generating optimal waveforms subject to this new constraint is presented, and the performance of the resulting waveforms is compared with those obtained using existing optimization techniques.     

Low sidelobe radar waveforms derived from orthogonal matrices

Novel waveforms are described that have low sidelobes when individual or multiple waveforms are approximately processed. They are related to orthogonal matrices that may be associated with complementary sequences and also with periodic waveforms having autocorrelation functions with constant zero-amplitude sidelobes. Also described are sets of sequences whose cross-correlation functions sum to zero everywhere. A potential application is the elimination of ambiguous range stationary clutter     

Optimum Signals for High-Resolution Radio Transmission Systems

This paper reports on progress in signal design that has led to improvedresolution capability in radar and communication systems without theuse of complicated signal-processing techniques.Two approaches to the problem of improving resolution capabilityare made. The first approach emphasizes the need to produce sharplypeaked autocorrelation functions. The optimum signal amplitude infrequency is specified to accomplish this, and the spectral density ofthe deterministic signal is shown to satisfy a homogeneous Wiener-Hopfequation. The second approach emphasizes the need to producelow and flattened cross-correlation functions, in order to distinguishthem (since they correspond to error outputs) from the sharply peakedautocorrelation functions. With the use of stationary phase integration,a detailed method for producing any desired cross-correlationamplitude is presented. In particular, the techniques necessary to producesinusoidally modulated cross-correlation functions are discussed.These tools are applied to a realistic N-signal processing system,and the resulting optimum signals are shown to be amplitude-modulatedchirped sinusoids. Detailed examples for physically justifiablesystem parameters are included.     

Cross-correlation properties of algebraically constructed Costasarrays

The problem of determining the cross-correlation properties of signals based on algebraically constructed Costas arrays is addressed by examining the discrete cross-correlation of the algebraically constructed Costas arrays for a given construction and dimension. Finding two arrays that minimally correlate implies that the signals based on these arrays also minimally correlate. The properties of finite fields are reviewed, and the major algebraic constructions for Costas arrays are presented, i.e. the Welch construction and the Golomb construction. The discrete cross-correlation properties of the Costas arrays are derived for arrays of the same dimension derived from the same construction. The use of Costas arrays in the signal design problem is discussed, and examples are given to show the cross-correlation of the signals based on the algebraically constructed arrays     

Control and utilization of range-dependent beampattern with waveform diverse array radars

The transmit antenna beampattern of the phased array radar is only a function of angle, limiting its ability to discriminate the targets from the same direction. Recently, the waveform diverse array radars expand the angle-dependent beampattern to an angle-time-range-dependent three-dimensional function by modulating the frequencies/time delays/phases across different transmit antenna elements. In this respect, extra Degrees-of-Freedom (DOFs) in the range domain are achieved, which opens up an innovative way to fulfil the tasks with enhanced system performance by jointly using the angle and range information. This paper summaries the developments of waveform diverse radars, including the Frequency Diverse Array (FDA), the Space-Time-Circulating-Array (STCA), and the Element-Pulse-Coding (EPC) frameworks, with emphasis on the analysis of the range-dependent beampattern from the basic properties upon how it is controlled. Moreover, the most recent advances of utilizing such a range-dependent beampattern in target detection, parameter estimation and identifiability, clutter suppression, jammer suppression and Synthetic Aperture Radar (SAR) imaging are discussed.     

Performance of a Modified Applebaum Adaptive Array

The performance of a modified Applebaum adaptive array is studied. The new array is obtained by removing the desired signal component from the output signal fed back to the correlator of an Applebaum type adaptive array. Various signal scenarios, including single desired signals or multiple simultaneous desired signals are examined. The new array is less sensitive to beam pointing errors and does not cause power inversion of desired signals. In the case of multiple simultaneous desired signals, the new array does not degrade the SNRs of strong desired signals.     

Robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels

The observer-based robust fault detection and optimization for a network of unmanned vehicles with imperfect communication channels and norm bounded modeling uncertainties are addressed. The network of unmanned vehicles is modeled as a discrete-time uncertain Markovian jump system. Based on the model, a residual generator is constructed and the sufficient condition for the existence of the desired fault detection filter is derived in terms of linear matrix inequality. Furthermore, a time domain optimization approach is proposed to improve the performance of the fault detection system. The problem of detecting small faults can be formulated as an optimization problem and its solution is given. For preventing false alarms, a new adaptive threshold function is established. The combined fault detection and optimization algorithm and the adaptive threshold are then applied to a network of highly maneuverable technology vehicles to illustrate the effective- ness of the orooosed aooroach.     

Track-to-track fusion with dissimilar sensors

An analysis is described of a kinematic state vector fusion algorithm when tracks are obtained from dissimilar sensors. For the sake of simplicity, it is assumed that two dissimilar sensors are equipped with nonidentical two-dimensional optimal linear Kalman filters. It is shown that the performance of such a track-to-track fusion algorithm can be improved if the cross-correlation matrix between candidate tracks is positive. This cross-correlation is introduced by noise associated with target maneuver that is common to the tracking filters in both sensors and is often neglected. An expression for the steady state cross-correlation matrix in closed form is derived and conditions for positivity of the cross-correlation matrix are obtained. The effect of positivity on performance of kinematic track-to-track fusion is also discussed     

Optimum Signals for Radar

The research reported herein deals with the general problem of the selection of radar waveforms. The investigation is specifically concerned with the synthesis of radar signals which are optimum in the sense that they are characterized by ambiguity surfaces minimized over certain predetermined regions of the ambiguity plane. The weighted ambiguity surface is utilized as the weighted error criterion. This error criterion is mathematically tractable and pertinent to radar system performance but is not unduly restrictive as some orientation parameters are left unspecified for subsequent cost or penalty function analysis. The signal optimization is approached by variational techniques augmented by equality and inequality constraints, for example, limiting the amount of bandwidth or frequency modulation to be less than some system requirement. Several examples are presented demonstrating the optimization techniques and providing a minimum error for the stated problem. It is shown that for any given type of amplitude modulation of the radar signal, the variance or dispersion of the ambiguity surface is not decreased for any type of phase modulation added. The optimum signal for an elliptical weighting function is derived for several cases. The minimum error is shown to depend upon the constraints and the unspecified orientation parameters and, for one case, on the second moment of the signal.     

Codes cross-correlation analysis and data/pilot code pairs optimization for Galileo E1 OS and GPS L1C

The Galileo E1 open service (OS) and the global positioning system (GPS) L1C are intending to use the multiplexed binary offset carrier (MBOC) modulation in E1/L1 band, including both pilot and data components. The impact of data and pilot codes cross-correlation on the distortion of the discriminator function (i.e., the S-curve) is investigated, when only the pilot (or data) components of MBOC signals are tracked. It is shown that the modulation schemes and the receiver configuration (e.g., the correlator spacing) strongly affect the S-curve bias. In this paper, two methods are proposed to optimize the data/pilot code pairs of Galileo E1 OS and GPS L1C. The optimization goal is to obtain the minimum average S-curve bias when tracking only the pilot components a the specific correlator spacing. Figures of merit, such as S-curve bias, correlation loss and code tracking variance have been adopted for analyzing and comparing the un-optimized and optimized code pairs. Simulation results show that the optimized data/pilot code pairs could significantly mitigate the intra-channel codes cross-correlation, and then improve the code tracking performance of MBOC signals.     

Ambiguity resolution of multiple targets using pulse-Dopplerwaveforms

To cancel clutter, both medium-PRF waveforms which are ambiguous in both range and Doppler and high-PRF waveforms which are ambiguous in range but unambiguous in ambiguities, a previous paper has shown that superior results for a single target can be achieved by using a clustering algorithm. Here, the problem of multiple targets is considered. A maximum likelihood (ML) technique which incorporates the clustering algorithm is developed for the multiple target problem. Simulation results show that four targets which have the same speed but are at different ranges can be resolved by using a medium-PRF waveform and employing the ML resolution technique     

基于解析梯度的微推进转移轨道优化方法

 研究基于离散脉冲策略的行星际微推进转移轨道优化问题,为改善收敛性和计算效率,提出了一种解析的梯度矩阵计算方法。首先,基于离散脉冲思想建立了行星际微推进转移轨道优化模型,通过对速度脉冲矢量进行参数变换,避免了传统优化模型初值猜测和搜索域难以界定的缺点;然后,基于变分原理分析了离散脉冲模型中轨道状态转移矩阵与状态变分之间的关系,并给出了多种轨道特征条件下状态变分的计算方法,该方法可扩展到多次状态不连续情况;在此基础上,推导了离散脉冲轨道优化模型中性能指标与轨道约束对寻优参数梯度矩阵的解析表达式。以地球-火星的燃料最省微推进转移为例对所提解析梯度方法进行了仿真验证。数值结果表明：本文推导的解析梯度矩阵是正确的,与传统数值梯度计算方法相比,解析梯度矩阵可有效改善寻优算法的收敛特性,并能够提高计算效率约47%。     

基于位势函数的欠定盲源分离识别诊断方法

对观测器数目小于源信号数目的欠定盲源分离进行了研究,提出了一种基于位势函数的稀疏信号欠定盲源分离方法,该方法从能量的观点出发,通过构造位势函数,将寻找混合信号在直线方向上的聚类问题转化为寻找累积位势函数的局部极大值问题,从而准确的估计出源信号数目和混合矩阵,克服了通常的基于k-means聚类的混合矩阵估计法需预先给定源信号数目的缺点.利用仿真信号检验了该方法的有效性.基于信号频域稀疏性假设,将该方法应用于欠定条件下的滚动轴承振动故障信号的盲分离,较好地分离出了故障信号.      

An efficient algorithm for multisensor track fusion

An efficient algorithm for track-to-track fusion by incorporating cross-covariance between tracks created by dissimilar sensors is described. An analytical solution of this problem is complicated if cross-correlation between sensors tracking the same target is taken into account. An explicit solution of the cross-covariance matrix at steady state is derived in terms of an integral. It is shown that solution of this integral involves inversion of a matrix whose elements are functions of parameters of individual trackers. Structure of this matrix is analyzed. An efficient analytical solution for inversion of this matrix is obtained. For fusion of similar sensors, it is shown that this matrix is reduced to the Routh-Hurwitz matrix which arises in the study of steady state stability of linear systems. Numerical results showing the amount of reduction of fused track covariance by taking into account the effects of cross-correlation between candidate tracks for fusion is also presented     

On the Ambiguity Function of Random Binary-Phase-Coded Waveforms

The ambiguity function of truly random binary-phase-coded waveforms, as an approximation to those waveforms commonly employed in binary-modulated pseudonoise systems/encoded radar systems, is investigated. In a statistical sense, the ambiguity function is analytically derived in which the normally used deterministic cross-correlation process is replaced by its ensemble average. Various Doppler filter responses are presented and discussed. The results are compared with those obtained by transmitting an aperiodic maximum length pseudorandom sequence. It is shown that the ambiguity function of the latter case is closely represented by the ensemble-average response of the truly random binary signal.     

Optical fiber wavelength division multiplexing

During flight, aircraft avionics transmit and receive RF signals to/from antennas over coaxial cables. As the density and complexity of onboard avionics increases, the electromagnetic interference (EMI) environment degrades proportionately, leading to decreasing signal-to-noise ratios (SNRs) and potential safety concerns. The coaxial cables are inherently lossy, limiting the RF signal bandwidth while adding considerable weight. To overcome these limitations, we have investigated a fiber optic communications link for aircraft that utilizes wavelength division multiplexing (WDM) to support the simultaneous transmission of multiple signals (including RF) over a single optical fiber. Optical fiber has many advantages over coaxial cable, particularly lower loss, greater bandwidth, and immunity to EMI. In this paper, we demonstrate that WDM can be successfully used to transmit multiple RF signals over a single optical fiber with no appreciable signal degradation. We investigate the transmission of FM and AM analog modulated signals, as well as FSK digital modulated signals, over a fiber optic link (FOL) employing WDM. We present measurements of power loss, delay, SNR, carrier-to-noise ratio (CNR), total harmonic distortion (THD), and bit error rate (BER). Our experimental results indicate that WDM is a fiber optic technology suitable for avionics applications.     

Decorrelation of broadband signals by Toeplitz-Block-Toeplitzstructuring

We propose F-norm of the cross-correlation part of the array covariance matrix as a measure of correlation between the impinging signals and study the performance of different decorrelation methods in the broadband case using this measure. We first show that dimensionality of the composite signal subspace, defined as the number of significant eigenvectors of the source sample covariance matrix, collapses in the presence of multipath and the spatial smoothing recovers this dimensionality. Using an upper bound on the proposed measure, we then study the decorrelation of the broadband signals with spatial smoothing and the effect of spacing and directions of the sources on the rate of decorrelation with progressive smoothing. Next, we introduce a weighted smoothing method based on Toeplitz-block-Toeplitz (TBT) structuring of the data covariance matrix which decorrelates the signals much faster than the spatial smoothing. Computer simulations are included to demonstrate the performance of the two methods     

FrFT-CSWSF:Estimating cross-range velocities of ground moving targets using multistatic synthetic aperture radar

Estimating cross-range velocity is a challenging task for space-borne synthetic aperture radar（SAR）, which is important for ground moving target indication（GMTI）. Because the velocity of a target is very small compared with that of the satellite, it is difficult to correctly estimate it using a conventional monostatic platform algorithm. To overcome this problem, a novel method employing multistatic SAR is presented in this letter. The proposed hybrid method, which is based on an extended space-time model（ESTIM） of the azimuth signal, has two steps： first, a set of finite impulse response（FIR） filter banks based on a fractional Fourier transform（FrFT） is used to separate multiple targets within a range gate; second, a cross-correlation spectrum weighted subspace fitting（CSWSF） algorithm is applied to each of the separated signals in order to estimate their respective parameters. As verified through computer simulation with the constellations of Cartwheel, Pendulum and Helix, this proposed time-frequency-subspace method effectively improves the estimation precision of the cross-range velocities of multiple targets.     

一种稀疏阵列下的二维DOA估计方法

研究了稀疏阵列下二维波达方向（DOA）的估计问题,提出一种基于不动点迭代的空间谱估计（FPC-MUSIC）算法。首先建立基于矩阵填充的DOA估计信号模型,并验证该信号模型满足零空间性质（NSP）,其次通过不动点迭代算法将稀疏阵列信号恢复为完整信号,最后利用恢复信号估计二维DOA。该算法可在稀疏阵列下大幅度降低谱估计平均副瓣,在大幅度降低阵元数的同时具有较高的估计精度。计算机仿真表明：FPC-MUSIC算法可在稀疏阵列下准确估计二维DOA,验证了该算法的有效性和优越性。