This paper describes the implementation of an improved clutter suppression method for the multiple pulse repetition time (PRT) technique based on simulated radar data. The suppression method is constructed using maximum likelihood methodology in time domain and is called parametric time domain method (PTDM). The procedure relies on the assumption that precipitation and clutter signal spectra follow a Gaussian functional form. The multiple interleaved pulse repetition frequencies (PRFs) that are used in this work are set to four PRFs (952, 833, 667, and 513 Hz). Based on radar simulation, it is shown that the new method can provide accurate retrieval of Doppler velocity even in the case of strong clutter contamination. The obtained velocity is nearly unbiased for all the range of Nyquist velocity interval. Also, the performance of the method is illustrated on simulated radar data for plan position indicator (PPI) scan. Compared with staggered 2PRT transmission schemes with PTDM, the proposed method presents better estimation accuracy under certain clutter situations.
The velocity and range ambiguity [
Various techniques have been proposed to overcome this problem [
These techniques which used nonuniform time series make filtering of clutter from the radar signal more complicated. Standard clutter filters cannot be applied directly to the nonuniform sampling scheme. Banjanin and Zrnic [
In this work, we extend PTDM to
Assuming that
The staggered PRT method applies a pulse transmission sequence that changes intervals between
The autocorrelations calculated from return signal time series at lags
Two approaches have been introduced to deal with the velocity aliasing. One algorithm uses the ratio of autocorrelations [
If the argument of
Mostly,
The relationship between the measured true velocity and the estimated velocities
Finding the appropriate integers
Bringi and Chandrasekar [
The multivariate density function of
Assuming that Doppler spectra of clutter and precipitation obey Gaussian distribution, the observed spectrum of Doppler velocity
For
Using the multivariate density function (
The main task of this work is to discuss the accuracy of estimated velocity under different clutter conditions. So, different values of mean velocity, signaltonoise ratio (SNR), and cluttertosignal ratio (CSR) are chosen to generate the observed Doppler spectra. We select a periodic scheme with 4 different PRTs: 1050, 1200, 1500, and 1950
Parameters of the simulated radar signal.
Parameter  Value 

Wavelength (m)  0.03 
Mean velocity (m/s) 

CSR (dB)  20, 40 
SNR (dB)  20, 40 
Precipitation spectrum width (m/s)  4 
Clutter spectrum width (m/s)  0.25 
Noise power (dB)  20 
Using the loglikelihood function (
Range of unknown parameters.
Parameter  Range 

Mean velocity (m/s)  ( 
Clutter power (dB)  (0, 
Precipitation power (dB)  (0, 
Precipitation spectrum width (m/s)  (1, 5) 
Clutter spectrum width (m/s)  (0.1, 0.3) 
Noise power (dB)  ( 
The true velocity (solid line) versus estimated velocities (hollow dot) from 30 simulations when CSR = 20 dB and SNR = 40 dB using PTDM. The mean of estimated velocities of each input velocity is shown as a red asterisk character.
Standard deviation (solid line with hollow dot) and bias (dotted line with cross) of estimated velocities in Figure
The noise and clutter environment is complex and variable in radar detection. The simulation can be carried out through two cases. The first one describes the conditions near the radar. The ground clutter echoes have various intensities. The other one considers the situations far away from the radar where ground clutter can be neglected. The simulated data are collected in the Nyquist velocity interval.
In the first type of simulation, the CSR changes from −20 dB to 40 dB. SNR is fixed to +40 dB during the computation. Figure
Bias (a) and standard deviation (b) of velocity estimates for the 4PRT (solid line) and 2PRT (dashed line) with SNR = 40 dB using the PTDM.
The second simulation is implemented for 0 dB ≤ SNR ≤ 40 dB and CSR = −20 dB. In Figure
Bias (a) and standard deviation (b) of velocity estimates for the 4PRT (solid line) and 2PRT (dashed line) with CSR = −20 dB using the PTDM.
In order to test the effectiveness of the proposed method, the
Radial velocity estimated from simulated
Figures
Figures
In this paper, a technique applying the parametric time domain method to the
It is shown that the proposed method can effectively estimate Doppler velocity. Two cases are simulated to analyze the standard deviation and bias of measured velocities, which can help to compare the proposed method with 2PRT transmission schemes with PTDM. The first one describes a situation where SNR is fixed to 40 dB and CSR varies. The biases are nearly the same for both of the methods. As long as CSR is lower than 20 dB, the standard deviation of measured velocity using the proposed method are almost three times less than the 2PRT transmission schemes with PTDM. The second type of simulation is performed for CSR = −20 dB and 0 dB ≤ SNR ≤ 40 dB. The estimation error of measured velocities using the 4PRT schemes is much better than that given by the 2PRT schemes.
The PPI scan of measured velocity is built on simulated radar data with SNR = 40 dB and different CSRs. The results confirm that the proposed method not only solves Doppler velocity aliasing but also performs better in clutter suppression than 2PRT schemes with PTDM especially when CSR < 30 dB.
The future works will focus on finding the optimal
The authors declare that there are no conflicts of interest regarding the publication of this paper.
The authors wish to thank Dr. Wei Cheng for his continuous encouragement and support. The authors have benefited from inhouse reports and information provided to them by the members of the Graduate Innovation Experimental Center.