Abstract
Amplitude-comparison monopulse radar in tracking radar uses the tracking scheme of a monopulse radar to estimate the angle components of a target. The performance of the amplitude comparison monopulse radar under measurement uncertainty is analysed. Measurement noises are modelled as Gaussian random variables. Taylor series expansion is adopted to get analytic expression of the mean square error (MSE). Estimation accuracy, in terms of the MSEs for estimate the direction-of-arrival (DOA) estimation algorithm, is usually obtained from the Monte Carlo simulation, which can be computationally intensive especially for large number of repetitions in the Monte Carlo simulation. To get reliable MSE in the Monte Carlo simulation, the number of repetitions should be very large, which implies that there is a trade-off between reliability of the MSE and computational burden in the Monte Carlo simulation. This paper shows the performance of amplitude comparison monopulse radar by linear approximation of nonlinear equations to estimate the DOA. The performance of amplitude comparison monopulse radar is quantitatively analysed via the MSEs, and the derived expression is validated by comparing the analytic MSEs with the simulation based MSEs. In addition, it is shown in the numerical results that analytically derived MSE is much less computationally intensive in comparison with the Monte Carlo simulation-based MSE, which implies that the proposed scheme in this paper results in drastic reduction in computational complexity for evaluation of the MSE.
Highlights
Radar can be largely divided into search and tracking radar depending on function
In comparison with the previous studies on the performance analysis of the amplitude comparison monopulse algorithm [13,15,16,17,18,19,20], we present a more explicit representation of the mean square error (MSE) in this paper
Our contribution in this paper lies in a reduction in computational cost in getting the MSE of an existing amplitude comparison monopulse algorithm by adopting analytic approach, rather than the Monte Carlo simulation-based MSE under measurement uncertainty due to an additive Gaussian noise
Summary
Radar can be largely divided into search and tracking radar depending on function. Search radar is used to locate targets within a relatively wide space, and the target information acquired is the distance, azimuth and elevation of the target. Monopulse is algorithm of estimating the angular location of a target by receiving a signal from a target by multiple antennas and comparing amplitude and phase. The author suggested to use an adaptive angle estimator, which would make its DOA estimate based on the received signal pulse and on the previously observed covariance statistics of the noises present at the four beam outputs. An algorithm for estimating DOA, based on the outputs of adaptively distorted sum and difference monopulse beams, is shown to perform well in the presence of sidelobe and/or main beam interference. Our contribution in this paper lies in a reduction in computational cost in getting the MSE of an existing amplitude comparison monopulse algorithm by adopting analytic approach, rather than the Monte Carlo simulation-based MSE under measurement uncertainty due to an additive Gaussian noise.
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