Position estimation error performance model for a minimum configuration 3-D multilateration

A multilateration system estimates the position of emitter using time difference of arrival (TDOA) measurements with a lateration algorithm. It involves solving a set of hyperbolic plane equations to determine the position of the emitter given the TDOA measurements that corresponds to the path difference (PD) measurement in distance. A performance model is developed using the relative maximum error bound (RMEB) which relates the plane equation condition number, the relative ground receiving station (GRS) geometry and the PD measurement error to estimate the position estimation (PE) error. By using air traffic monitoring for civil aviation as an application, Monte Carlo simulation verifies the PE error of the performance model for a square GRS configuration. The coverage assumed a 3600 bearing, a range of up to 200 km and a maximum altitude of 15 km. Simulation results also show that the performance model estimates the horizontal position error with a maximum absolute error of 0.1 km up to a range of 200 km at an altitude of 15 km and a minimum absolute error of 0.2 km at an altitude of 15 km

Position estimation bias analysis of a multilateration system with a reference station selection technique

Multilateration (MLAT) system estimates the position of an aircraft using Time Difference of Arrival (TDOA) measurements estimated at spatially located Ground Receiving Station (GRS) pairs with a lateration algorithm. The Position Estimation (PE) accuracy of an MLAT system depends on several factors, one of which is the choice of reference station used to generate the TDOA estimations for use with the lateration algorithm. Furthermore, the closed-form lateration algorithm is known to introduce bias in the PE process. Thus, a bias analysis and improvement in the PE accuracy of an MLAT system with a reference selection technique is presented in the paper. The analysis is carried out for a square GRS configuration with each GRS equipped with a receiver whose Time of Reception (TOR) error Standard Deviation (SD) is assumed 1 nsec. Monte Carlo simulation result of lateration algorithm with reference selection technique shows a reduction of at least 75 % in both the overall PE Mean Square Error (MSE) and bias. Furthermore, the PE Root Mean Square Error (RMSE) obtained by the lateration algorithm is reduced by at least 50 % out of which 36 % of the reduced PE RMSE is contributed only by the TOR estimation error

P-wave and s-wave estimation for GPS derived seismic signal

The availability of GPS (Global Positioning System) provides an alternative technology to seismography to detect earthquakes and detect their epicenters. However, the limited sampling rate and processing errors could potentially reduce the accuracy for estimating the required signal parameters. This paper evaluates the methods for analysing GPS derived seismic signals from the 2004 Sumatra Andaman Earthquake based on their timerepresentation, power spectrum and time-frequency representation. Between the three representations, the parameters of the earthquake signals such as P-wave and S-wave are clearly represented on the time-frequency representation

Analysis and classification of airborne radar signal types using time-frequency analysis

An electronic support (ES) system is used by the military for intelligence gathering, threat detection, and as a support to the electronic attack system. Its main feature is to determine the frequency parameters and pulse characteristics of the received radar signal. The estimated signal parameters are then used as input to a classifier network to determine the identity of the received signal. This paper describes airborne radar signal type analysis and classification (ARTAC) system that uses the spectrogram to obtain the time-frequency representation (TFR) and apply analysis tools such as the instantaneous energy, instantaneous frequency and other related tools to estimate various signal parameters. The estimated parameters are used as input to the rule-based classifier which classifies the signal appropriately. Monte-Carlo simulation is then carried out to determine the accuracy of signal classification at various signal-to-noise ratios (SNRs) in additive white Gaussian noise (AWGN). The method used achieves 90 percent classification accuracy at SNR of 6.2dB

Classification of digitally modulated signals using cross time-frequency distribution

Signal classification is important in a wide range of application and various researches had been carried out. This is a challenging task especially in the non-cooperative environment where there is no information of the received signal available. Therefore, time-frequency analysis is applied to extract the signal parameters received off the air. The estimated parameters are then used as the input to the classifier at which the accuracy of the classification will depends greatly on the parameter estimations. This paper proposed the cross time-frequency distribution (XFTD) to classify various type of digitally modulated signals such as ASK, FSK, PSK and QAM signals. It is shown that the XTFD is capable to give above 90% classification accuracy at a minimum SNR of -2 dB. The XTFD is superior to noise and is capable to cover a wide range of signals including digitally phase modulated signals

Discriminating closely spaced aircrafts using time difference of arrival (TDOA) based association algorithm

A time difference of arrival (TDOA) based locating system determines the location of an aircraft by measuring the time difference between transponder emissions received at ground station antenna (GSA) pairs. To locate multiple aircrafts, the TDOAs are first grouped according to each aircraft using an association algorithm prior to the individual aircraft locating process. The ability to correctly associate the TDOAs to the right aircraft depends on the received signal to noise ratio (SNR) and the separation between the aircraft. For a given horizontal range, azimuth and altitude separation between an aircraft pair, a technique is developed to evaluate an association algorithm capability to group the measured TDOAs to the correct aircraft. The performance of the association algorithm considers three different military flying formations using emissions from the onboard weapon control radar (WCR) and replies to a secondary surveillance radar (SSR) interrogator. The simulation results show that with the technique, it is possible to determine the probability of correct association of the estimated TDOAs to the right aircraft by the association algorithm. Furthermore, based on a horizontal range and azimuth separations of 50 m and an altitude separation of 1,000 ft, the TDOA based locating system coupled with the association algorithm has the best locating performance using TDOAs obtained from emissions through the main lobe of the WCR antenna

Experimental multipath delay profile of underwater acoustic communication channel in shallow water

The shallow water channel is an environment that is of particular interest to many research fields. An underwater acoustic channel is characterized as a multipath channel. Time-varying multipath propagation is one of the major factors that limit the acoustic communication performance in shallow water. This study conducts two underwater acoustic experiments in Tanjung Balau, Johor, Malaysia. A transducer and a hydrophone are submerged at different depths and separated by different distances. Linear frequency modulated (LFM) pulses are chosen as the main transmit signal for the experiments. The crosscorrelation between the transmitted and received signals represents the impulse response of the channel (multipath profile). The results show that the amplitude of the successive paths will not rapidly decline, and vice versa, when the distance between the sender and the receiver increases. Moreover, the time difference between the different paths will be small in the case of distance increase. In other words, the successive paths will converge in time

Test register insertion at RTL based on reduced BIST

Built-in self-test (BIST) method has high area overhead and long test application time. In this paper, a new BIST method is proposed at register transfer level (RTL) as a design for testability (DFT) method to modify a given RTL circuit to a reduced BISTable RTL circuit. First, we introduce modelling method called extended R-graph to represent the register connectivity of an RTL circuit. The original register in the RTL circuit is modified into multiple input signature registers (MISRs) as test register. The selection of MISR is performed by extended minimum feedback vertex set (MFVS) algorithm that identifies a set of vertices (representing test register) which breaks all the loops of extended R-graph with minimal cost when vertices are removed. It has been proven through simulation that the proposed BIST method has lower area overhead of 32.9% on average and achieves comparably high fault coverage compared to the previous method, concurrent BIST using ITC'99 benchmark circuits

Reliability of seismic signal analysis for earthquake epicenter location estimation using 1 Hz GPS kinematic solution

This paper proposed a reliable analysis method of Global Positioning System (GPS) derived seismic signal to locate the epicenter of a far-field regional earthquake. The surface wave of the seismic signal is utilized due to the attenuation in the body wave which is conventionally used in seismometer. The main contribution is the identification of time-frequency representation (TFR) as a signal analysis method to derive the time of arrival (TOA) for epicenter location estimation using multilateration technique. The comparison was made with other methods such as directly from the time representation, the instantaneous energy, and the power spectrum estimation. The data from the 2004 Sumatra Andaman earthquake captured from four GPS continuously operating reference stations (GPS CORS) were used in the analysis. To validate the accuracy of the proposed method, the estimated epicenter location was compared with the data released by the United States Geological Survey (USGS). The estimated location shows an error of about 0.0572 degrees (6.3 km) in latitude and 0.2848 degrees (31.33 km) in longitude. This is comparable to previous studies using seismometer with an average error of 25 km for far field earthquakes and 20 km for recent work on GPS derived seismic signals for near field earthquakes

Enhancement of power measurement by decimation in 1/f noise

The assumption of additive white Gaussian noise (AWGN) to model measurement is not valid since many applications such as in RF power measurement the noise is colored with 1/f spectrum characteristics. With this characteristics, the assumption of independently identically distribution (IID) used in signal detection and estimation becomes not valid. The autocorrelation function and power spectrum can be used to characterize both the AWGN and 1/f noise. By the process of decimation, the 1/f noise can be converted to AWGN. Monte Carlo simulation for power measurement in 1/f noise has shown that the decimation reduces the variance by about 11 times. The decimation process has successfully converted real noise signals that consist of 1/f noise and AWGN to AWGN. Thus, the decimation method works for practical applications