Using EMD-FrFT filtering to mitigate high power interference in chirp tracking radars

This letter presents a new signal processing subsystem for conventional monopulse tracking radars that offers an improved solution to the problem of dealing with manmade high power interference (jamming). It is based on the hybrid use of empirical mode decomposition (EMD) and fractional Fourier transform (FrFT). EMD-FrFT filtering is carried out for complex noisy radar chirp signals to decrease the signal's noisy components. An improvement in the signal-to-noise ratio (SNR) of up to 18 dB for different target SNRs is achieved using the proposed EMD-FrFT algorithm

Fractional fourier transform based monopulse radar for combating jamming interference

Monopulse radars are used to track a target that appears in the look direction beam width. The distortion produced when manmade high power interference (jamming). Jamming scenarios are achieved by introducing high power interference to the radar processor through the radar antenna main lobe (main lobe interference) or antenna side lobe (side lobe interference). This leads to errors in the target tracking angles that may cause target mistracking. A new monopulse radar structure is presented in this paper which offers a solution to this problem. This structure is based on the use of optimal Fractional Fourier Transform (FrFT) filtering. The proposed system configurations with the optimum FrFT filters is shown to reduce the simulated interfered signal and improve the signal to noise ratio (SNR) in the processors outputs in both processor using the proposed monopulse structure

Enhanced monopulse radar tracking using fractional Fourier filtering in the presence of interference

Monopulse radars are used to track a target that appears in the look direction beam width. Significant distortion is produced when manmade high power interference (jamming) is introduced to the radar processor through the radar antenna main lobe (main lobe interference) or antenna side lobe (side lobe interference). This leads to errors in the target tracking angles that may cause target mistracking. A new monopulse radar structure is presented in this paper which addresses this problem. This structure is based on the use of optimal Fractional Fourier Transform (FrFT) filtering. The improved performance of the new monopulse radar structure over the traditional monopulse processor is assessed using standard deviation angle estimation error (STDAE) for a range of simulated environments. The proposed system configurations with the optimum FrFT filters is shown to reduce the interfered signal and to minimize the STDAE for monopulse processors

Enhanced monopulse radar tracking using empirical mode decomposition

Monopulse radar processors are used to track targets that appear in the look direction beamwidth. The target tracking information (range, azimuth angle, and elevation angle) are affected when manmade high power interference (jamming) is introduced to the radar processor through the radar antenna main lobe (main lobe interference) or antenna side lobe (side lobe interference). This interference changes the values of the error voltage which is responsible for directing the radar antenna towards the target. A monopulse radar structure that uses filtering in the empirical mode decomposition (EMD) domain is presented in this paper. EMD is carried out for the complex radar chirp signal with subsequent denoising and thresholding processes used to decrease the noise level in the radar processed data. The performance enhancement of the monopulse radar tracking system with EMD based filtering is included using the standard deviation angle estimation error (STDAE)

A new fractional Fourier transform based monopulse tracking radar processor

Conventional monopulse radar processors are used to track a target that appears in the look direction beam width. The distortion produced when additional targets appear in the look direction beam width can cause severe erroneous outcomes from the monopulse processor. This leads to errors in the target tracking angles that may cause the target tracker to fail. A new signal processing algorithm is presented in this paper that is based on the use of optimal Fractional Fourier Transform (FrFT) filtering to solve this problem. The relative performance of the new filtering method over traditional based methods is assessed using standard deviation angle estimation error (STDAE) for a range of simulated environments. The proposed system configurations with the optimum FrFT filters succeeds in effectively cancelling additional target signals appearing in the look direction beam width

Radar matched filtering using the fractional fourier transform

Abstract-A matched filter is the optimal linear filter for maximizing the signal to noise ratio (SNR) in the presence of additive noise. Matched filters are commonly used in radar systems where the transmitted signal is known and may be used as a replica to be correlated with the received signal which can be carried out by multiplication in the frequency domain by applying Fourier Transform (FT). Fractional Fourier transform (FrFT) is the general case for the FT and is superior in chirp pulse compression using the optimum FrFT order. In this paper a matched filter is implemented for a chirp radar signal in the optimum FrFT domain. Mathematical formula for a received chirp signal in the frequency domain and a generalized formula in the fractional Fourier domain are presented in this paper using the Principle of Stationary Phase (PSP). These mathematical expressions are used to show the limitations of the matched filter in the fractional Fourier domain. The parameters that affect the chirp signal in the optimum fractional Fourier domain are described. The performance enhancement by using the matched filter in the fractional Fourier domain for special cases is presented

Fractional fourier transform based matched filtering for target detection in chirp radars

This article discusses fractional fourier transform based matched filtering for target detection in chirp radars

Optimum fractional fourier filtering for monopulse processors distortion

Conventional monopulse radar processors are used to track a target that appears in the look direction beam width. The distortion produced when additional targets appear in the look direction beam width can cause severe erroneous outcomes from the monopulse processor. This leads to errors in the target tracking angles that may cause the target tracker to fail. A new signal processing algorithm is presented in this paper that is based on the use of optimal Fractional Fourier Transform (FrFT) filtering to solve this problem. The relative performance of the new filtering method over traditional based methods is assessed using standard deviation angle estimation error (STDAE) for a range of simulated environments. The proposed system configurations with the optimum FrFT filters succeeds in effectively cancelling additional target signals appearing in the look direction beam width even if these target have the same Doppler frequency