scholarly journals Direct Instantaneous Frequency Rate Estimation to Improve the Carrier Estimation Performance in Mars Entry, Descent, and Landing Flight

2018 ◽  
Vol 10 (8) ◽  
pp. 1259 ◽  
Author(s):  
Wanhong Hao ◽  
Xiaowei Cui ◽  
Jianguang Feng ◽  
Guangliang Dong ◽  
Zhiyong Zhu
Keyword(s):  
Instantaneous Frequency ◽  
Search Algorithm ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Current Approach ◽  
Estimation Accuracy ◽  
Cubic Phase ◽  
Estimation Performance ◽  
Frequency Rate ◽  
Coherent Integration

This paper focuses on the carrier estimation performance improvement in Mars entry, descent, and landing (EDL) flights. Carrier reconstruction could be used for trajectory derivation and Martian atmosphere profile inversion, and is the critical information for mission operations, as it helps determine the flight status of the spacecraft, demodulate the downlink information. The current approach is maximum likelihood estimation based on a two-dimensional (2D) maximum energy search algorithm, which computes the grid energy over all the combinations of frequency cells and frequency rate cells among the search space. Although it has good performance on robust estimation, the frequency estimation accuracy is limited due to the short coherent integration. An instantaneous frequency rate tracking approach based on the cubic phase function (CPF) is proposed that directly estimates the instantaneous frequency rate over the frequency rate cells, followed by the frequency estimation among the frequency cells. A sequential estimation method is introduced to propose the sequential CPF statistics, which uses the a priori Doppler phase information to suppress the noise squaring loss inherent in the standard CPF statistics. Simulations have been made on the released Mars Science Laboratory EDL trajectory for the two approaches, which show that considerable estimation improvement has been achieved for aerobraking flight by the new algorithm.

scholarly journals Detection of LFM Radar Signals and Chirp Rate Estimation Based on Time-Frequency Rate Distribution

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5415
Author(s):  
Ewa Swiercz ◽  
Dariusz Janczak ◽  
Krzysztof Konopko
Keyword(s):  
Parameter Estimation ◽  
Instantaneous Frequency ◽  
Estimation Methods ◽  
Joint Analysis ◽  
Cubic Phase ◽  
Chirp Rate ◽  
Time Frequency ◽  
Rate Estimation ◽  
Detection And Estimation ◽  
Frequency Rate

Linear frequency-modulated (LFM) signals are the most significant example of waveform used in low probability of intercept (LPI) radars, synthetic aperture radars and modern communication systems. Thus, interception and parameter estimation of the signals is one of the challenges in Electronic Support (ES) systems. The methods, which are widely used to accomplish this task are mainly based on transformations from time to time-frequency domain, which concentrate the energy of signals along an instantaneous frequency (IF) line. The most popular examples of such transforms are the short time Fourier transform (STFT) and Wigner-Ville distribution (WVD). However, for LFM waveforms, methods that concentrate signal energy along a line in the time-frequency rate domain may allow to obtain better detection and estimation performance. This type of transformation can be obtained using the cubic phase (CP) function (CPF). In the paper, the detection of LFM waveform and its chirp rate (CR) parameter estimation based on the extended forms of the standard CPF is proposed. The CPF was originally introduced for instantaneous frequency rate (IFR) estimation for quadratic frequency modulated (QFM) signals i.e., cubic phase signals. Summation or multiplication operations on time cross-sections of the CPF allow to formulate the extended forms of the CPF. Based on these forms, detection test statistics and the estimation procedure of LFM signal parameters have been proposed. The widely known estimation methods assure satisfying accuracy for high SNR levels, but for low SNRs the reliable estimation is a challenge. The proposed approach based on joint analysis of detection and estimation characteristics allows to increase the reliability of chirp rate estimates for low SNRs. The results of Monte-Carlo simulation investigations on LFM signal detection and chirp rate estimation evaluated by the mean squared error (MSE) obtained by the proposed methods with comparisons to the Cramer-Rao lower bound (CRLB) are presented.

scholarly journals Estimation Method of SAR Doppler Frequency Rate Based on FrFT

2020 ◽  
Vol 38 (6) ◽  
pp. 1352-1360
Author(s):  
Ying Chen ◽  
Tao Chen ◽  
Kewei Li ◽  
Julan Xiao ◽  
Hongli Liu
Keyword(s):  
Present Method ◽  
Pulse Compression ◽  
Estimation Method ◽  
Doppler Frequency ◽  
Real Data ◽  
Estimation Accuracy ◽  
Optimal Order ◽  
Maximum Point ◽  
Frequency Rate ◽  
Strong Scattering

Due to the problem that the existing Doppler frequency rate estimation method is limited by the estimation accuracy, a novel estimation method of Doppler frequency rate is proposed. The present method searches the frequency rate according to the characteristic of the chirp signal in the FrFT domain. Firstly, dechirp is performed on several strong scattering points extracted from the data domain after pulse compression, and a frequency domain focused image is obtained after FFT. Then the maximum point of each distance unit is extracted. The energy of the maximum point is selected by using the window processing. After that, IFFT is performed and the dechirp conjugate reference function is multiplied by using the selected points. FrFT is performed according to the preset orders. The entropy is used to evaluate whether the order of FRFT is optimal or not. The Doppler frequency rate is calculated by using the optimal order. The simulation and real data are processed and analyzed. The present method can estimate the Doppler frequency rate accurately. A well-focused SAR image is obtained after azimuth matching filtering.

scholarly journals Experimental and Analytical Studies on Improved Feedforward ML Estimation Based on LS-SVR

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Xueqian Liu ◽  
Hongyi Yu
Keyword(s):  
Frequency Estimation ◽  
Additive White Gaussian Noise ◽  
Estimation Method ◽  
Threshold Value ◽  
Small Sample ◽  
Support Vector ◽  
Linear Filter ◽  
Ml Estimation ◽  
Single Tone ◽  
Estimation Performance

Maximum likelihood (ML) algorithm is the most common and effective parameter estimation method. However, when dealing with small sample and low signal-to-noise ratio (SNR), threshold effects are resulted and estimation performance degrades greatly. It is proved that support vector machine (SVM) is suitable for small sample. Consequently, we employ the linear relationship between least squares support vector regression (LS-SVR)’s inputs and outputs and regard LS-SVR process as a time-varying linear filter to increase input SNR of received signals and decrease the threshold value of mean square error (MSE) curve. Furthermore, it is verified that by taking single-tone sinusoidal frequency estimation, for example, and integrating data analysis and experimental validation, if LS-SVR’s parameters are set appropriately, not only can the LS-SVR process ensure the single-tone sinusoid and additive white Gaussian noise (AWGN) channel characteristics of original signals well, but it can also improves the frequency estimation performance. During experimental simulations, LS-SVR process is applied to two common and representative single-tone sinusoidal ML frequency estimation algorithms, the DFT-based frequency-domain periodogram (FDP) and phase-based Kay ones. And the threshold values of their MSE curves are decreased by 0.3 dB and 1.2 dB, respectively, which obviously exhibit the advantage of the proposed algorithm.

Sign in / Sign up

Export Citation Format

Share Document