Time-frequency represetation of radar signals using Doppler-Lag block searching Wigner-Ville distribution

Radar signals are time-varying signals where the signal parameters change over time. For these signals, Quadratic Time-Frequency Distribution (QTFD) offers advantages over classical spectrum estimation in terms of frequency and time resolution but it suffers heavily from cross-terms. In generating accurate Time-Frequency Representation (TFR), a kernel function must be able to suppress cross-terms while maintaining auto-terms energy especially in a non-cooperative environment where the parameters of the actual signal are unknown. Thus, a new signal-dependent QTFD is proposed that adaptively estimates the kernel parameters for a wide class of radar signals. The adaptive procedure, Doppler-Lag Block Searching (DLBS) kernel estimation was developed to serve this purpose. Accurate TFRs produced for all simulated radar signals with Instantaneous Frequency (IF) estimation performance are verified using Monte Carlo simulation meeting the requirements of the Cramer-Rao Lower Bound (CRLB) at SNR > 6 dB

Emitter velocity estimation comparison for frequency difference of arrival measurement based single and multiple reference lateration algorithm

The accuracy at which the instantaneous velocity and position of a non-stationary emitting source estimated using a lateration algorithm depends on several factors such as the lateration algorithm approach, the number and choice of reference receiving station (RS) used in developing the lateration algorithm. In this paper, the use of multiple reference RSs was proposed to improve the velocity estimation accuracy of the frequency difference of arrival (FDOA) based lateration algorithm. The velocity estimation performance of the proposed multiple reference FDOA based lateration algorithm is compared with the conventional approach of using single reference RS at some selected emitter positions using Monte Carlo simulation. Simulation result based on an equilateral triangle RS configuration shows that the use of multiple reference RSs improved the velocity estimation accuracy of the lateration algorithm. Based on the selected emitter positions, a reduction in velocity estimation error of about 0.033m/s and 1.31 m/s for emitter positions at ranges 0.5 km and 5 km respectively was achieved using the multiple reference lateration algorithm

FPGA implementation of multi frequency continuous phase frequency shift keying (MCPFSK) modulation techniques for HF data communication

In HF (High Frequency) data communication systems [1,2], FSK (Frequency Shift Keying) digital modulation is widely used. The simplicity in the implementation is the main reason for its popularity. Since noncoherent detection is possible, additional components such as timing recovery circuits [3] are not necessary as required in PSK (Phase Shift Keying) modulation

Power quality analysis using frequency domain smooth-windowed Wigner-Ville distribution

Power quality has become a great concern to all electricity consumers. Poor power quality can cause equipment failure, data and economical losses. An automated monitoring system is needed to ensure signal quality, reduce diagnostic time and rectify failures. This paper presents the analysis of power quality signals using frequency domain smooth-windowed Wigner-Ville distribution (FDSWWVD). The power quality signals focused are swell, sag, interruption, harmonic, interharmonic and transient based on IEEE Std. 1159-2009. The TFD represents signal jointly in time-frequency representation (TFR) with good frequency and time resolution. Thus, it is very appropriate to analyze the signals that consist of multi-frequency components and magnitude variations. However, there is no fixed kernel of the TFD can be used to remove cross-terms for all types of signals. A set of performance measures is defined and used to compare the TFRs to identify and verify the TFD that operated at optimal kernel parameters. The result shows that FDSWWVD offers good performance of TFR and appropriate for power quality analysis

Direct and indirect TDOA estimation based multilateration system position estimation accuracy comparison

Multilateration (MLAT) system estimate aircraft position from its electromagnetic emission using time difference of arrival (TDOA) estimated at ground receiving station (GRS)s with a lateration algorithm. The position estimation (PE) accuracy of the MLAT system depends on several factors one of which is the TDOA estimation approach. In this paper, the PE performance of a minimum configuration 3-dimensional (3-D) MLAT system based on the direct and indirect approaches to TDOA estimation is presented. The analysis is carried out using Monte Carlo simulation with the transmitter and receiver parameters based on an actual system used in the civil aviation. Simulation results show that within 150 km radius, the direct TDOA based MLAT system performs better than the indirect TDOA based MLAT system. Beyond 150 km radius, the indirect TDOA based MLAT system has the least PE error compared the direct TDOA based MLAT system. Further comparison of the MLAT system based on the two TDOA estimation approaches with other surveillance systems shows that the direct TDOA based MLAT system has the least PE error within 150 km radius while long-range aircraft PE beyond 150 km, automatic surveillance dependent broadcast (ADS-B) outperformed the MLAT system as it has the least PE error

Performance of site velocity prediction in Sundaland

Global Positioning System (GPS) technique has been extensively implemented in determination of crustal deformation globally. With the ability of providing solution up to milimeter (mm) level, this technique has proven to provide a precise estimate of site velocity that represents the actual motion of tectonic plate over a period. Therefore, this study aims to evaluate the site velocity estimation from GPS-derived daily position of station, respective to the global plate motion model and predicted site velocity via Least-Squares Collocation (LSC) method within the tectonically active region of Sundaland. The findings have indicated that stations with precise velocity estimates were consistent with global plate model and predicted velocity, with velocity residuals of 5 mm - 10 mm. However, stations that were severely impacted by continuous earthquake events such as in Sumatra were believed to be induced by the impact with consistently large velocity residuals up to 37 mm. Following the outcomes, this study has provided an insight on the post-seismic decay period plate motion which are induced by continuous tectonic activities respective to modelled plate motion

Adaptive window size and stepped frequency scan spectrogram analysis for drone signal detection in multi-signal environment

In this paper, a spectrogram based on stepped frequency scanning and adaptive window size algorithm is proposed to detect drone signals that operate at the 2.4 and 5.8 GHz Industrial, Scientific and Medical (ISM) bands in a multi-signal environment. In this algorithm, the received signal is divided into multiple sub-bands and scanned through a large analysis bandwidth. The window size is automatically adjusted by balancing the time and frequency resolution. The adaptive stepped frequency scan spectrogram (ASFSS) is then implemented to obtain the time-frequency representation (TFR). From the TFR, signal parameters, such as the hop duration, bandwidth, and instantaneous frequency (IF), are estimated. Three possible drone signal types are used in the study: fast frequency hopping spread spectrum (FHSS), slow FHSS, and hybrid spread spectrum (HSS). The performance of ASFSS is verified using Monte-Carlo simulation with 20 realisations at signal-to-noise ratio (SNR) range from-16 to 12 dB. In the presence of additive white Gaussian noise (AWGN), the detection cut-off point is-12 dB for fast and slow FHSS and-5 dB for HSS. Additional environment signals, such as direct sequence spread spectrum (DSSS) and WiFi, increase the cut-off point to 5 dB for fast FHSS, 7 dB for slow FHSS and 8 dB for HSS

Window selection for the multi-window periodogram spectrum estimation and spectrogram time-frequency analysis

The concept of multi-window or multi-taper spectral estimation was discussed in [1]-[5]. This is performed by averaging the spectrum of the signal modulated with any set of orthogonal windows [1], such as minimum bias windows, sinusoidal windows and the sequence of discrete prolate spheroids or the Slepian sequence [2]. The Slepian sequence is the most common orthogonal set of windows used in the spectral analysis. It was first introduced in [3] where it is applied to stationary spectral analysis. It is shown in [4] that this technique have better performance in terms of variance, leakage and resolution as compared to the weighted overlapped segment averaging method (Welch periodogram)