Giftet Inc.

Worcester, MA, United States

Giftet Inc.

Worcester, MA, United States

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Wang G.H.,Yantai Naval Aeronautical and Astronautical University | Chen L.,Yantai Naval Aeronautical and Astronautical University | Jia S.Y.,Yantai Naval Aeronautical and Astronautical University | Progri I.,Giftet Inc.
Journal of Navigation | Year: 2013

For mobile 3-D radar installed on a gyro-stabilized platform, its measurements are usually contaminated by the systematic biases which contain radar offset biases (i.e., range, azimuth and elevation biases) and attitude biases (i.e., yaw, pitch and roll biases) of the platform because of the errors in the Inertial Measurement Units (IMU). Systematic biases can NOT be removed by a single radar itself; however, fortunately, they can be estimated by using two different radar measurements of the same target. The process of estimating systematic biases and then compensating radar measurements is called error registration. In this paper, the registration models are established first, then, the equivalent radar measurement error expressions caused by the attitude biases are derived and the dependencies among attitude biases and offset biases are analysed by using the observable matrix criterion. Based on the analyses above, an Optimized Bias Estimation Model (OBEM) is proposed for registration. OBEM uses the subtraction of azimuth and yaw bias as one variable and omits roll and pitch biases in the state vector, which decreases the dimension of the state vector from fourteen of the All Augmented Model (AAM), (which uses all the systematic biases of both radars as state vector) to eight and has about 80% reduction in calculation costs. Also, OBEM can decrease the coupling influences of roll and pitch biases and improve the estimation performance of radar elevation bias. Monte Carlo experiments were made. Numerical results showed that the bias estimation accuracies and the rectified radar raw measurement accuracies can be improved. Copyright © The Royal Institute of Navigation 2012.


Chen L.,Yantai Naval Aeronautical and Astronautical University | Wang G.H.,Yantai Naval Aeronautical and Astronautical University | He Y.,Yantai Naval Aeronautical and Astronautical University | Progri I.,Giftet Inc.
Journal of Navigation | Year: 2014

For mobile radars installed on a gyro-stabilised platform (GSP) that can steadily follow an East-North-Up (ENU) frame, attitude biases (ABs) of the platform and offset biases (OBs) of the radar are linear dependent variables. Therefore ABs and OBs are unobservable in the linearized registration equations; however, when combining them as new variables, the system becomes observable, and this model has been called the unified registration model (URM). Unlike GSP mobile radars, un-stabilised GSP (or UGSP) mobile radars are installed on the platform directly and rotate with the platform simultaneously. For UGSP, it is testified that both types of biases are independent and observable because the time-varying attitude angles (AAs) 1 of the platform are included in the registration equations, which destroy the dependencies of both kinds of biases and lead us to propose a completely different linearized registration model- the All Augmented Model (AAM). AAM employs all OBs and ABs in the state vector and a Kalman filter (KF) to produce their estimates. Numerical simulation results show that the estimated performance of AAM is close to the Cramér-Rao lower bound (CRLB) and that the Root Mean Square Errors (RMSEs) of the rectified measurements by using AAM are more than 500Â m smaller than by URM in all directions. Copyright © The Royal Institute of Navigation 2013 Â.


Chen L.,Yantai Naval Aeronautical and Astronautical University | Wang G.H.,Yantai Naval Aeronautical and Astronautical University | Progri I.F.,Giftet Inc.
Journal of Electrical and Computer Engineering | Year: 2014

For mobile radar, offset biases and attitude biases influence radar measurements simultaneously. Attitude biases generated from the errors of the inertial navigation system (INS) of the platform can be converted into equivalent radar measurement errors by three analytical expressions (range, azimuth, and elevation, resp.). These expressions are unique and embody the dependences between the offset and attitude biases. The dependences indicate that all the attitude biases can be viewed as and merged into some kind of offset biases. Based on this, a unified registration model (URM) is proposed which only contains radar "offset biases" in the form of system variables in the registration equations, where, in fact, the "offset biases" contain the influences of the attitude biases. URM has the same form as the registration model of stationary radar network where no attitude biases exist. URM can compensate radar offset and attitude biases simultaneously and has minor computation burden compared with other registration models for mobile radar network. © 2014 Lei Chen et al.


Chen L.,Yantai Naval Aeronautical and Astronautical University | Wang G.H.,Yantai Naval Aeronautical and Astronautical University | Jia S.Y.,Yantai Naval Aeronautical and Astronautical University | Progri I.,Giftet Inc.
Journal of Navigation | Year: 2012

Besides offset biases (such as range, the gain of range, azimuth, and elevation biases), for mobile radars, platform attitude biases (such as yaw, pitch, and roll biases) induced by the accumulated errors of the Inertial Measurement Units (IMU) of the Inertial Navigation System (INS) can also influence radar measurements. Both kinds of biases are coupled. Based on the analyses of the coupling influences and the observability of 3-D radars error registration model, in the article, an Attitude Bias Conversion Model (ABCM) based on Square Root Unscented Kalman Filter (SRUKF) is proposed. ABCM can estimate 3-D radars absolute offset biases under the influences of platform attitude biases. It converts platform attitude biases into radar measurement errors, by which the target East-North-Up (ENU) coordinates can be obtained from radar measurements directly without using the rotation transformation, which was usually used in the transition from platform frame to ENU considering attitude biases. In addition, SRUKF can avoid the inaccurate estimations caused by linearization, and it can weaken the adverse influences of the poor attitude bias estimation results in the application of ABCM. Theoretical derivations and simulation results show that 1) ABCM-SRUKF can improve elevation bias estimate accuracy to about 0•8 degree in the mean square error sense; 2) linearization is not the main reason for poor estimation of attitude biases; and 3) unobservability is the main reason. © 2012 The Royal Institute of Navigation.


Progri I.F.,Giftet Inc. | Huang P.,University of Electronic Science and Technology of China | Pi Y.,University of Electronic Science and Technology of China | Xia X.,Huazhong University of Science and Technology
Institute of Navigation International Technical Meeting 2016, ITM 2016 | Year: 2016

Indoors, GNSS signal encounters severe multipath power loss and fading which leads to significant signal degradation of the amplitude and phase to perform GPS (or GNSS) signal acquisition. To overcome these effects, piling up received GPS (or GNSS) data is a traditional (or conventional) method; however, it exhibits two shortcomings (drawbacks or limitations): instable detection performance, such as the probability of false alarm (PFA) fluctuates due to changes of the signal-to-noise ratio (SNR); and elongated acquisition time caused by extended accumulation duration and over repetitive FA occurrence (or "penalty"). To overcome the first shortcoming, an adaptive structure is employed in GNSS signal acquisition that enables constant FA rate (CFAR) criteria to guarantee a stable detection performance on the GNSS signal acquisition. To overcome the second shortcoming, an adaptive determination on accumulation length is employed to minimize the accumulation duration; therefore, a double-dwell structure (DDS) is used to reduce the processing time "penalty" caused by FA. Simulation results illustrate that an adaptive, stable detection implementation and DDS reduce the average acquisition time by almost fifty percent (or by half or a factor of two). Other important significant unique accomplishments found in this paper are as follows: Dr. Progri for the first time provides the closed form expressions of generalized modified Bessel function distributions of the cumulative distribution functions (cdf) of the first and second kinds and for the first time introduces the very powerful utility of the Kampé de Fériet function and parabolic cylinder function in the navigation community. © 2016 by Institute of Navigation. All right reserved.


Huang P.,University of Electronic Science and Technology of China | Pi Y.,University of Electronic Science and Technology of China | Progri I.,Giftet Inc.
Journal of Navigation | Year: 2013

In some Global Positioning System (GPS) signal propagation environments, especially in the ionosphere and urban areas with heavy multipath, GPS signal encounters not only additive noise but also multiplicative noise. In this paper we compare and contrast the conventional GPS signal acquisition method which focuses on handling GPS signal acquisition with additive noise, with the enhanced GPS signal processing under multiplicative noise by proposing an extension of the GPS detection mechanism, to include the GPS detection model that explains detection of the GPS signal under additive and multiplicative noise. For this purpose, a novel GPS signal detection scheme based on high order cyclostationarity is proposed. The principle is introduced, the GPS signal detection structure is described, the ambiguity of initial PseudoRandom Noise (PRN) code phase and Doppler shift of GPS signal is analysed. From the simulation results, the received GPS signal at low power level, which is degraded by additive and multiplicative noise, can be detected under the condition that the received block of GPS data length is at least 1·6 ms and sampling frequency is at least 5 MHz. Copyright © 2012 The Royal Institute of Navigation.


Progri I.F.,Giftet Inc.
Proceedings of the Annual Precise Time and Time Interval Systems and Applications Meeting, PTTI | Year: 2014

This paper presents the complete original definition of first generation Variable Binary Offset Carrier generalized multidimensional geolocation modulation waveforms, to improve the standardization of the United States DoD GPS, European Galileo, Russian GLONASS, Chinese Compass, Indian IRNSS in the L-band (1-2 GHz), and the United Nations International Telecommunications Union (ITU) GNSS or geolocation waveforms in the S-band (2-4 GHz) and C-band (4-8 GHz). In the paper it is argued that the selection of BOC(1,1) on the GPS L1 civil data code and BOC(10,5) (or the military code or M-Code) on both GPS L1 and L2 frequencies is entirely arbitrary because BOC modulation is a special case of for or ; hence, all the current state-of-the-art GNSS waveforms exhibit sub-optimal signal design performance even at the end-user when generalized global objective functions are applied. pure signal design or broad definition of generalized autocorrelation function (ACF) and power spectral density (PSD) offers a unique signal design methodology and provides the necessary framework for ACF pure signal optimization to fill in substantial signal design gaps; hence, improving the GNSS signal design and standardization. Index Terms-Pulse generation, pulse amplitude modulation, pulse width modulation, multidimensional sequences, signal design, signal analysis, generalized functions, time-frequency analysis, minimization methods, optimization methods.


Progri I.F.,Giftet Inc.
Institute of Navigation International Technical Meeting 2015, ITM 2015 | Year: 2015

This paper examines common optimization algorithms, such as sum and mean square sense applied to the optimization of the autocorrelation functions (ACF) of GPS M-code like signals such as the variable binary offset carrier (VBOC). Before the different versions are examined for efficiency, on GPS M-code like signals such as VBOC2 which vary with the parameter of signal design and optimization alpha, they are checked to make sure that their corresponding ACFs are valid via a set of conditions known as continuity theorems. Afterwards, by employing any of the optimization algorithms such as sum and mean square sense on GPS M-code like signals such as VBOC2 we are able to produce ACFs that are one ninety four percent more efficient than the corresponding ACFs of the GPS M-code signals.


Progri I.F.,Giftet Inc.
Institute of Navigation International Technical Meeting 2015, ITM 2015 | Year: 2015

This paper presents the complete original definition of first generation Variable Binary Offset Carrier VB0C2(α, 1-α) generalized multidimensional geolocation modulation waveforms, to improve the standardization of the United States DoD GPS, European Galileo, Russian GLONASS, Chinese Compass, Indian IRNSS in the L-band (1-2 GHz), and the United Nations International Telecommunications Union (ITU) GNSS or geolocation waveforms in the S-band (2-4 GHz) and C-band (4-8 GHz). In the paper it is argued that the selection of BOC(10,5) (or the military code or M-Code) on both GPS LI and L2 frequencies is entirely arbitrary because BOC modulation is a special case of VBOC2(α, 1-α) for α = 0 or α - 1; hence, all the current state-of-the-art GNSS waveforms exhibit sub-optimal signal design performance even at the end-user when generalized global objective functions are applied. VB0C2(α, 1 - α) pure signal design or broad definition of generalized autocorrelation function (ACF) and power spectral density (PSD) offers a unique signal design methodology and provides the necessary framework for VBOC2(α, 1 - α) ACF pure signal optimization to fill in substantial signal design gaps; hence, improving the GNSS signal design and standardization.


Progri I.F.,Giftet Inc.
Institute of Navigation International Technical Meeting 2016, ITM 2016 | Year: 2016

This paper examines common optimization algorithms, such as sum, product, and minimum mean square error (MMSE) sense applied to the optimization of the autocorrelation functions (ACF) of GPS L1C and M-code like signals such as the variable binary offset carrier (VBOC). Before the different versions are examined for efficiency, on GPS L1C and M-code like signals such as VBOC1 which vary with the parameter of signal design and optimization alpha, they are checked to make sure that their corresponding ACFs are valid via a set of conditions known as continuity theorems. Afterwards, by employing any of the optimization algorithms such as sum, product, and MMSE on GPS L1C and M-code like signals such as VBOC1 we are able to produce ACFs that are one hundred percent more efficient than the corresponding ACFs of the GPS L1C and M-code signals. © 2016 by Institute of Navigation. All right reserved.

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