Blind GPS receiver with a modified despreader for interference suppression

The global positioning system (GPS) was designed to provide location estimates for various civilian and military applications using at least four satellites. Since GPS signals have a low signal-to-noise ratio (SNR), they also have a low signal-to-jammer ratio so that the accuracy of location estimates is influenced by cochannel interference and intentional jammers. We propose a low-complexity blind adaptive receiver that is based on a novel modified despreader and the constant modulus (CM) array. This system is capable of ing directional interference and capturing the GPS signal of interest without requiring explicit angle-of-arrival (AOA) information. We also consider the multiple satellite problem and extend the proposed receiver to capture several GPS signals of interest. Representative computer simulation examples are presented to illustrate the performance of the multicomponent system for the suppression of different jammer types.     

Multicomponent receiver architectures for GPS interference suppression

The global positioning system (GPS) is a one-way satellite-based navigation system employing spread-spectrum techniques that is widely used for commercial and military applications. Although the very low signal-to-noise ratio (SNR) is handled by the large spreading gain, GPS is susceptible to high-power interference signals and various types of jammers. We propose multicomponent receiver architectures for GPS interference suppression. A conventional antenna system is first considered which utilizes a minimum-variance distortionless-response (MVDR) beam former and assumes that the GPS signal angle of arrival (AOA) and the antenna model are known at the receiver. However, this receiver is sensitive to AOA estimation errors and can have a high computational complexity. This sensitivity problem is eliminated by a multicomponent system based on a multistage matched filter (MF). Since this MF receiver also has a high computational complexity because the jammer AOAs must be estimated, we introduce a blind interference canceler based on the constant modulus (CM) array that is insensitive to AOA estimation errors and has a low computational complexity. Computer simulations are provided to illustrate the performance of the various systems for interference suppression in example signal scenarios.     

STAP for GPS receiver synchronization

A space-time adaptive processing (STAP) algorithm for delay tracking and acquisition of the GPS signature sequence with interference rejection capability is developed. The interference can consist of both broadband and narrowband jammers, and is mitigated in two steps. The narrowband jammers are modelled as vector autoregressive (VAR) processes and rejected by temporal whitening. The spatial ing is implicitly achieved by estimating a sample covariance matrix and feeding its inverse into the extended Kalman filter (EKF). The EKF estimates of the code delay and the fading channel are used for a t-test for acquisition detection. Computer simulations demonstrate robust performance of the algorithm in severe jamming, and also show that the algorithm outperforms the conventional delay-locked loop (DLL).     

基于Kalman滤波的GPS/INS接收机自适应干扰抑制方法

 考虑到惯导信息辅助GPS(GPS/INS)接收机对干扰抑制实时性的要求,提出一种基于Kalman滤波的GPS/INS接收机自适应干扰抑制方法。自适应广义旁瓣相消(GSC)多采用低复杂度最小均方(LMS)算法更新权矢量,收敛速率较低,严重时会导致接收机定位中断。首先利用Householder变换构建GSC下支路的阻塞矩阵,用于阻塞任意二维阵型阵列接收的期望信号;再用Kalman滤波自适应更新下支路权矢量,从而有效提高阵列输出信干噪比(SINR)。理论分析和仿真结果说明本文方法可有效抑制干扰对接收机的影响,且具有实时性高的特点。     

Single Sidelobe Canceller: Theory and Evaluation

A sidelobe canceller (SLC) can be efficiently employed to reduce the undesirable effects of jammers on a search radar system. In this paper a functional block circuit is described for a single-sidelobe canceller (SSLC) apt to a single Jammer suppression; a detailed analysis is also presented. It is shown that the theory of stochastic differential equations and the covariance analysis describing function (CADET) technique can be used to evaluate the SSLC performances when two Gaussian colored and mutually correlated input processes are considered. The statistical properties of the weight can be obtained. The last results, which are very important in the case of nonstationary jammers, cannot be obtained without this theory. System implications can be drawn from the abovementioned analysis when the input process consists of one jammer or two jammers and/or thermal noise.     

Hierarchical adaptive Kalman filtering for interplanetary orbitdetermination

A modular and flexible approach to adaptive Kalman filtering has recently been introduced using the framework of a mixture-of-experts regulated by a gating network. Each expert is a Kalman filter modeled with a different realization of the unknown system parameters. The unknown or uncertain parameters can include elements of the state transition matrix, observation mapping matrix, process noise covariance matrix, and measurement noise covariance matrix. The gating network performs on-line adaptation of the weights given to individual filters based on performance. The mixture-of-experts approach is extended here to a hierarchical architecture which involves multiple levels of gating. The proposed architecture provides a multilevel hypothesis testing capability. The utility of the hierarchical architecture is illustrated via the problem of interplanetary navigation (Mars Pathfinder) using simulated radiometric data. It serves as a useful tool for assisting navigation teams in the process of selecting the parameters of the navigational filter over various operating regimes. It is shown that the scheme has the capability of detecting changes in the system parameters and switching filters appropriately for optimal performance. Furthermore, the expectation-maximization (EM) algorithm is shown to be applicable in the proposed framework     

Real-time navigation using the global positioning system

This paper presents the results of an investigation of the application of the Global Positioning System (GPS) to real-time integrated missile navigation. We present quantifiable measures of navigation accuracy as a function of GPS user segment parameters. These user segment parameters include antenna phase response accuracy, single versus dual frequency, and Kalman filter structure and size. We also formulate some new phase-locked loop (PLL) filter designs for application in GPS receivers, and demonstrate their superiority over more conventional filters     

Analysis of upgraded GPS internal Kalman filter

GPS receivers with provisions for inertial navigation system (INS) aiding are designed with internal Kalman filters that model generic INSs and process the basic GPS pseudorange and deltarange (range-rate) data to produce an output of inertially-smoothed, “GPS-derived” position and velocity. These Kalman filters model only the basic nine INS errors (position, velocity, and tilt) and do not model any INS gyro or accelerometer errors. It was found that a significant performance improvement could be achieved under conditions of degraded GPS satellite availability by augmenting this type of filter with the six INS gyro and accelerometer bias errors. It is, therefore, recommended that serious consideration be given to incorporating these states into the design of the GPS internal Kalman filter     

Multistatic adaptive pulse compression

A new technique denoted as multistatic adaptive pulse compression (MAPC) is introduced which exploits recent work on adaptive pulse compression (APC) in order to jointly separate and pulse compress the concurrently received return signals from K proximate multistatic radars operating (i.e., transmitting) within the same spectrum. For the return signal from a single pulse of a monostatic radar, APC estimates the particular receive filter for a given range cell in a Bayesian sense reiteratively by employing the matched filter estimates of the surrounding range cell values as a priori knowledge in order to place temporal (i.e., range) nulls at the relative ranges occupied by large targets and thereby suppress range sidelobes to the level of the noise. The MAPC approach generalizes the APC concept by jointly estimating the particular receive filter for each range cell associated with each of several concurrently-received radar return signals occupying the same spectrum. As such, MAPC is found to enable shared-spectrum multistatic operation and is shown to yield substantial performance improvement in the presence of multiple spectrum-sharing radars as compared with both standard matched filters and standard least-squares mismatched filters     

A Gaussian Mixture PHD Filter for Jump Markov System Models

The probability hypothesis density (PHD) filter is an attractive approach to tracking an unknown and time-varying number of targets in the presence of data association uncertainty, clutter, noise, and detection uncertainty. The PHD filter admits a closed-form solution for a linear Gaussian multi-target model. However, this model is not general enough to accommodate maneuvering targets that switch between several models. In this paper, we generalize the notion of linear jump Markov systems to the multiple target case to accommodate births, deaths, and switching dynamics. We then derive a closed-form solution to the PHD recursion for the proposed linear Gaussian jump Markov multi-target model. Based on this an efficient method for tracking multiple maneuvering targets that switch between a set of linear Gaussian models is developed. An analytic implementation of the PHD filter using statistical linear regression technique is also proposed for targets that switch between a set of nonlinear models. We demonstrate through simulations that the proposed PHD filters are effective in tracking multiple maneuvering targets.     

Quadratic extended Kalman filter approach for GPS/INS integration

GPS/INS integration system has been widely applied for navigation due to their complementary characteristics. And the tightly coupled integration approach has the advantage over the loosely coupled approach by using the raw GPS measurements, but hence introduces the nonlinearity into the measurement equation of the Kalman filter. So the typical method for navigation using measurements of range or pseudorange is by linearizing the measurements in an extended Kalman filter (EKF). However, the modeling errors of the EKF will cause the bias and divergence problems especially under the situation that the low quality inertial devices are included. To solve this problem, a quadratic EKF approach by adding the second-order derivative information to retain some nonlinearities is proposed in this paper. Simulation results indicate that the nonlinear terms included in the filtering process have the great influence on the performance of integration, especially in the case that the low quality INS is used in the integrated system. Furthermore, a two-stage cascaded estimation method is used, which circumvents the difficulty of solving nonlinear equations and greatly decreases the computational complexity of the proposed approach, so the quadratic EKF approach proposed in this paper is of great value in practice.     

A hardware-efficient, multirate, digital channelized receiverarchitecture

An approach is presented to realizing a digital channelized receiver for signal intercept applications that provides a hardware efficient implementation of a uniform filter bank in which the number of filters K is greater than the decimation factor M. The proposed architecture allows simple channel arbitration logic to be used and provides reliable instantaneous frequency measurements, even in adjacent channel crossover regions. In the proposed implementation of the filter bank, K is related to M by K=FM where F is an integer. It is shown that the optimum selection of F allows the instantaneous frequency measurement to be made in the channel crossover region and the arbitration function to be based solely on the instantaneous frequency measurement. The development of a filter bank structure which combines the flexibility of the short-time Fourier transform (STFT) with the implementation efficiency of the polyphase filter bank decomposition, meeting these requirements and leading to a hardware-efficient implementation, is presented     

GPS多径信号的自适应滤波估计方法

 研究全球定位系统(GPS)多径信号估计的问题。通过分析自适应滤波器的原理,建立了数字中频信号处理的数学模型,提出一种用自适应滤波实现GPS多径幅度、码相位和载波相位估计的方法。该方法采用不同延迟的伪随机序列对信号进行解扩、解调和累加,得到了作为期望信号的系列自适应滤波相关值。对该方法与其他3种方法进行了理论上的分析比较,得出本方法具有信噪比高、自适应滤波性能好、带有码相位信息和不存在载波模糊度问题等优点。根据各种滤波器算法的特点和本应用的需求,给出了选用递归最小二乘算法实现的方法。通过计算机仿真,验证了提出的方法能够在14 dB的信噪比下,以1个采样间隔的时间延迟分辨率和0.005周的载波相位估计精度估计出GPS L1的多径信号。     

Interrelationship of single-filter and multiple-model adaptivealgorithms

An equivalent filter bank structure for multiple model adaptive estimation (MMAE) is developed that uses the residual and state estimates from a single Kalman filter and linear transforms to produce equivalent residuals of a complete Kalman filter bank. The linear transforms, which are a function of the differences between the system models used by the various Kalman filters, are developed for modeling differences in the system input matrix, the output matrix, and the state transition matrix. The computational cost of this new structure is compared with the cost of the standard Kalman filter bank (SKFB) for each of these modeling differences. This structure is quite similar to the generalized likelihood ratio (GLR) structure, where the linear transforms can be used to compute the matched filters used in the GLR approach. This approach produces the best matched filters in the sense that they truly represent the time history of the residuals caused by a physically motivated failure model     

Subspace array processing for the suppression of FM jamming in GPS receivers

The mitigation of FM interference in GPS receivers is considered. In difference to commonly assumed wideband and narrowband interferers, the FM interferers are wideband, but instantaneously narrowband, and as such, have clear time-frequency (TF) signatures that are distinct from the GPS coarse acquisition (C/A) spread spectrum code. In the proposed technique, the estimate of the FM interference instantaneous frequency (IF) and the interference spatial signature are used to construct the spatiotemporal interference subspace. The IF estimates can be provided using existing effective linear or bilinear TF methods. The undesired signal arrival is suppressed by projecting the input data on the interference orthogonal subspace. With a multisensor receiver, the distinctions in both the spatial and TF signatures of signal arrivals allow effective interference suppressions. The deterministic nature of the signal model is considered and the known underlying structure of the GPS C/A code is utilized. We derive the receiver signal-to-interference-plus-noise ratio (SINR) under exact and perturbed IF values. The effect of IF estimation errors on both pseudorange measurements and navigation data recovery is analyzed. Simulation results comparing the receiver performances under IF errors in single and multiantenna GPS receivers are provided.     

A New Sampling Procedure for the Synthesis of Linear Transversal Filters

In linear transversal filters for signal processing, the impulse response of the filter is syntheszed in a sampled form by means of a tapped delay line with weighted and summed taps. The synthesis procedure consists of sampling the specified impulse response at appropriate intervals and using the sample values as the tap weights. A nonuniform sampling procedure for the synthesis of the impulse response is introduced, which can produce results more conveniently than the classical Shannon sampling procedure because of the simplicity of the transversal filter implementation. According to the new procedure, in the time domain the samples are taken at points where the instantaneous phase of the impulse response is a multiple of ir radians. The spectral distribution which ensues in the frequency domain consists of a series of spectra all having the same fractional bandwidth. The transversal filters synthesized by this sampling criterion are referred to as phase-sampled impulse response (PSIR) filters. An important application of PSI R filters is to the generation and matched filtering of a large class of AM and FM waveforms.     

A minimax approach to the design of Doppler filters

The detection of a target in correlated clutter, thermal noise, and extraneous interference is considered. The amplitude, phase and Doppler frequency of the signal are not known a priori. A general criterion is presented which measures the performance of a suboptimal test relative to an optimal test. The criterion is encompassed into a design procedure used to design Doppler filters. The procedure allows many design considerations to be taken into account, and results in a design which attempts to minimize the number of filters required. For low dimensionality the procedure results in single filter designs; for higher dimensionality multiple filters are designed. The performances of these systems are compared with the results obtained by Emerson (1978) and Andrews (1974). It is found that the procedure yields good filter designs under general conditions and may reduce the number of filters required compared with classical designs     

组合导航系统中一种基于特征值分解的自适应信息融合滤波算法

基于分散滤波理论的联合滤波算法,可以有效地降低组合导航系统的计算负担,并且增强系统的容错性能。给出了一种联合滤波算法中信息分配系数的自适应计算方法,能够使联合系统根据导航过程中各传感器的信息质量的变化合理地反馈全局信息。仿真结果表明,该算法可以有效地降低由于导航子系统降级带来的滤波误差。     

航空发动机双重传感器故障诊断逻辑研究

针对航空发动机控制系统的双重传感器故障,提出了一种采用双路容错设计的卡尔曼滤波器故障检测隔离系统.故障检测隔离系统由一系列卡尔曼滤波器组成,每个滤波器都假定2路传感器故障,而以故障支路外的测量值作为输入量.当双重传感器故障发生时,只有不包含故障传感器信息的滤波器保持较低的估计残差,其他滤波器都会产生较大的估计残差,如此双重传感器故障便可以被隔离.利用滤波器组估计残差的特征,进一步设计合理的运算逻辑,系统就可以同时对传感器单一故障进行检测和隔离.为了验证故障诊断系统的有效性,在发动机慢车状态分别对传感器发生双重故障和单一故障的情况进行仿真.仿真结果表明:故障诊断系统能够准确有效地对传感器双重故障和单一故障进行检测和隔离.      

自适应高阶容积卡尔曼滤波在目标跟踪中的应用

针对传统容积卡尔曼滤波(CKF)在系统状态发生突变时估计精度下降的问题,将强跟踪滤波(STF)算法与高阶容积卡尔曼滤波(HCKF)算法相结合,提出了一种自适应高阶容积卡尔曼滤波(AHCKF)方法。该算法采用高阶球面-相径容积规则,可获得高于传统CKF的估计精度,同时在HCKF算法中引入STF,通过渐消因子在线修正预测误差协方差阵,强迫残差序列正交,提高了算法的鲁棒性,增强了算法应对系统状态突变等不确定因素的能力。将提出的AHCKF算法应用于具有状态突变的机动目标跟踪问题并进行数值仿真,仿真结果表明,AHCKF算法在系统状态发生突变的情况下表现出良好的滤波性能,有效地避免了状态突变造成的滤波精度下降,较传统的CKF、HCKF、交互式多模型-容积滤波(IMM-CKF)和自适应容积卡尔曼滤波(ACKF)算法有更强的鲁棒性和系统自适应能力。