Energetic particles and radar blackouts at Mars

2021 ◽  
Author(s):  
Mark Lester ◽  
Beatriz Sanchez-Cano ◽  
Daniel Potts ◽  
Rob Lillis ◽  
Marco Cartacci ◽  
...  
Keyword(s):  
Lower Ionosphere ◽  
Solar Energetic Particle ◽  
Lower Atmosphere ◽  
Radar Signal ◽  
Density Peak ◽  
Surface Reflection ◽  
Average Spectrum ◽  
Apparent Relationship ◽  
Radar Echo ◽  
Human Exploration

<p>We present the first long-term characterization of the lower ionosphere of Mars, a region previously inaccessible to orbital observations, based on an analysis of radar echo blackouts observed by MARSIS on Mars Express and SHARAD on the Mars Reconnaissance Orbiter from 2006 to 2017.  A blackout occurs when the expected surface reflection is partly to fully attenuated for portions of an observation.  Enhanced ionization at altitudes of 60 to 90 km, below the main ionospheric electron density peak, results in the absorption of the radar signal, leading to a radar blackout.  MARSIS, operating at frequencies between 1.8 and 5 MHz suffered more blackouts than SHARAD, which has a higher carrier frequency (20 MHz).  More events are seen during solar maximum while  there is no apparent relationship between blackout occurrence and crustal magnetic fields. Blackouts do occur during both nightside and dayside observations, and have an interesting variation with solar zenith angle.   Analysis of MAVEN Solar Energetic Particle (SEP) electron counts between 20 and 200 keV during selected events demonstrates that these electrons are responsible for such events, and we investigate the minimum SEP electron fluxes required to ionize the lower atmosphere and produce  measurable attenuation.  When both radars observe a radar blackout at the same time, the SEP electron fluxes are at their highest. For certain events, we find that the average spectrum responsible for a blackout is particularly enhanced at the higher energy end of the spectrum, i.e. above 70 keV .   This study is, therefore, important for future communications for human exploration of Mars.</p>

A Statistical Analysis of Radar Blackouts at Mars: MARSIS, SHARAD and MAVEN Observations

2020 ◽  
Author(s):  
Mark Lester ◽  
Beatriz Sanchez-Cano ◽  
Daniel Potts ◽  
Rob Lillis ◽  
Roberto i Orosei ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Solar Minimum ◽  
Solar Maximum ◽  
Radar Signal ◽  
Solar Cycles ◽  
Instrumental Reason ◽  
Density Peak ◽  
Surface Reflection ◽  
Average Spectrum ◽  
Flux Energy

<p>We present an analysis of radar blackouts observed by MARSIS on Mars Express and SHARAD on Mars Reconnaissance Orbiter for the interval 2006 – 2017.  The period of interest encompasses the extended solar minimum between solar cycles 23 and 24 as well as the solar maximum of cycle 24.  Blackouts have been identified by eye through scanning daily plots of the surface reflection for both radars.  A blackout occurs when, for no apparent instrumental reason, the surface reflection normally expected is either not observed (total) or when the surface reflection is seen for only part of the orbit or the surface reflection is both weaker and spread over a significant time delay (partial).  Such blackouts are caused by enhanced ionisation at altitudes below the main ionospheric electron density peak resulting in increased absorption of the radar signal.  There are more occurrences observed by MARSIS than SHARAD, which is expected due to the lower absorption at the higher operating frequency of SHARAD.  We also observe more blackouts during solar maximum than solar minimum.  Indeed, there are no total blackouts during the extended solar minimum, although both radars do have partial blackouts.  There is no apparent relationship between blackout occurrence and crustal magnetic fields.  Following previous work, which has indicated that solar energetic particles, specifically electrons are responsible for the enhanced ionisation in the atmosphere, we also present the analysis of the MAVEN SEP electrons between 20 keV and 2 MeV during events when all three spacecraft were operational.  We find that the SEP electron flux-energy relationship is much enhanced during the total blackouts, in particular where both radars are impacted, while for partial blackouts the flux-energy spectrum is closer to those from orbits where no blackout occurs.  We also find that for certain events, the average spectrum which result in a blackout is particularly enhanced at the higher energy end of the spectrum, above 50 keV. The average spectra from each condition is presented.  We conclude that there is a higher probability of a radar blackout during solar maximum, that crustal magnetic fields play no apparent role in the their observational occurrence, that the higher energy (< 50 keV) electrons are responsible, and that for events where both radars observe a radar blackout the SEP electron fluxes are at their highest.</p>

scholarly journals Compressed Sensing Reconstruction of Radar Echo Signal Based on Fractional Fourier Transform and Improved Fast Iterative Shrinkage-Thresholding Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Rui Zhang ◽  
Chen Meng ◽  
Cheng Wang ◽  
Qiang Wang
Keyword(s):  
Fourier Transform ◽  
Compressed Sensing ◽  
Fractional Fourier Transform ◽  
Radar Signal ◽  
Reconstruction Algorithms ◽  
Echo Signal ◽  
Time Frequency ◽  
Iterative Shrinkage ◽  
Radar Echo ◽  
Iterative Shrinkage Thresholding

The compressed sensing theory, which has received great attention in the field of radar technology, can effectively reduce the data rate of high-resolution radar imaging systems and solve the problem of collecting, storing, and transmitting large amounts of data in radar systems. Through the study of radar signal processing theory, it can be found that the echo of radar LFM transmit signal has sparse characteristics in the distance upward; based on this, we can consider using the theory of compressed sensing in the processing of radar echo to optimize the processing. In this paper, a fast iterative shrinkage-thresholding reconstruction algorithm based on protection coefficients is proposed. Under the new scheme, firstly, the LFM echo signal’s good sparse representation is obtained by using the time-frequency sparse characteristics of the LFM echo signal under the fractional Fourier transform; all reconstruction coefficients are analyzed in the iterative process. Then, the coefficients related to the feature will be protected from threshold shrinkage to reduce information loss. Finally, the effectiveness of the proposed method is verified through simulation experiments and application example analysis. The experimental results show that the reconstruction error of this method is lower and the reconstruction effect is better compared with the existing reconstruction algorithms.

Detection and Parameter Estimation for Chirp Signal Based on Fractional Fourier Transform

2014 ◽  
Vol 599-601 ◽  
pp. 1474-1477
Author(s):  
Xin Chen ◽  
Min Tao ◽  
Tian Tang Pan ◽  
Yan Li
Keyword(s):  
Parameter Estimation ◽  
Fractional Fourier Transform ◽  
Estimation Algorithm ◽  
Wave Parameter ◽  
Estimation Accuracy ◽  
Radar Signal ◽  
Chirp Signal ◽  
Computation Complexity ◽  
Maximum Value ◽  
Radar Echo

The Chirp signal has been used widely in radar signal, radar echo wave can established to be Chirp model. The estimation of radar echo wave parameter is a important task in radar signal processing. In this paper, we introduced three theories and algorithms of detection and estimation of Chirp signal: 2D peak searching algorithm, two steps searching of maximum value algorithm and pre-estimation algorithm firstly. The parameter estimation precision and computation complexity in low SNR was simulated for these three algorithms. The final simulation indicate that the two steps searching algorithm of maximum value take on nice estimation accuracy and low computation complexity in contrast.

Design and Implementation of a Phase-Coded Quasi-CW Radar Signal Processor

2010 ◽  
Vol 20-23 ◽  
pp. 785-790 ◽  
Author(s):  
Chao Wang ◽  
Feng Su ◽  
Yun Peng Han
Keyword(s):  
Random Phase ◽  
Radar Signal ◽  
Operation System ◽  
Time Operation ◽  
Radar Echo ◽  
Real Time Operation ◽  
Processing Platform ◽  
Cw Radar ◽  
Parallel Signal Processing ◽  
Signal Processor

A pseudo-random phase-coded quasi-CW radar signal processor is designed，and implemented based on a parallel signal processing platform. Distance sidelobe and “echo eclipse” are two problems inherent to the phase-coded quasi-CW radar. In this paper, “Code agility” method is used to suppress the distance sidelobe, which has good performance even when the radar echo is badly eclipsed. Software of the radar signal processor is characterized by pipelined processing, and the DSP program is based on real-time operation system. Results of the field experiment verify the correctness of our design.

scholarly journals The Mars Environmental Dynamics Analyzer, MEDA. A Suite of Environmental Sensors for the Mars 2020 Mission

2021 ◽  
Vol 217 (3) ◽  
Author(s):  
J. A. Rodriguez-Manfredi ◽  
◽  
M. de la Torre Juárez ◽  
A. Alonso ◽  
V. Apéstigue ◽  
...  
Keyword(s):  
Particle Size ◽  
Humidity Sensor ◽  
Atmospheric Temperature ◽  
Lower Atmosphere ◽  
Atmospheric Radiation ◽  
Environmental Sensors ◽  
Brightness Temperatures ◽  
Human Exploration ◽  
Scientific Purpose ◽  
Aerosol Properties

AbstractNASA’s Mars 2020 (M2020) rover mission includes a suite of sensors to monitor current environmental conditions near the surface of Mars and to constrain bulk aerosol properties from changes in atmospheric radiation at the surface. The Mars Environmental Dynamics Analyzer (MEDA) consists of a set of meteorological sensors including wind sensor, a barometer, a relative humidity sensor, a set of 5 thermocouples to measure atmospheric temperature at ∼1.5 m and ∼0.5 m above the surface, a set of thermopiles to characterize the thermal IR brightness temperatures of the surface and the lower atmosphere. MEDA adds a radiation and dust sensor to monitor the optical atmospheric properties that can be used to infer bulk aerosol physical properties such as particle size distribution, non-sphericity, and concentration. The MEDA package and its scientific purpose are described in this document as well as how it responded to the calibration tests and how it helps prepare for the human exploration of Mars. A comparison is also presented to previous environmental monitoring payloads landed on Mars on the Viking, Pathfinder, Phoenix, MSL, and InSight spacecraft.

scholarly journals A Novel Density Peak Fuzzy Clustering Algorithm for Moving Vehicles Using Traffic Radar

Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 46
Author(s):  
Lin Cao ◽  
Yunxiao Liu ◽  
Dongfeng Wang ◽  
Tao Wang ◽  
Chong Fu
Keyword(s):  
Fuzzy Clustering ◽  
Clustering Algorithm ◽  
Cluster Center ◽  
Echo Signal ◽  
Density Peak ◽  
Fuzzy Clustering Algorithm ◽  
Moving Vehicles ◽  
Strong Robustness ◽  
Radar Echo ◽  
Density Peak Clustering

The detection of adjacent vehicles in highway scenes has the problem of inaccurate clustering results. In order to solve this problem, this paper proposes a new clustering algorithm, namely Spindle-based Density Peak Fuzzy Clustering (SDPFC) algorithm. Its main feature is to use the density peak clustering algorithm to perform initial clustering to obtain the number of clusters and the cluster center of each cluster. The final clustering result is obtained by a fuzzy clustering algorithm based on the spindle update. The experimental data are the radar echo signal collected in the real highway scenes. Compared with the DBSCAN, FCM, and K-Means algorithms, the algorithm has higher clustering accuracy in certain scenes. The average clustering accuracy of SDPFC can reach more than 95%. It is also proved that the proposed algorithm has strong robustness in certain highway scenes.

scholarly journals Performance Analysis of Data Transmission for Joint Radar and Communication Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jianhua Lu ◽  
Tuanwei Tian ◽  
Yanli Tang ◽  
Bin Tang
Keyword(s):  
Data Transmission ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Average Power ◽  
Spectrum Efficiency ◽  
Radar Signal ◽  
Interference Avoidance ◽  
Data Throughput ◽  
Radar Echo ◽  
Significant Performance

This paper investigates the problem of data transmission for the joint radar and communication systems (JRCSs). The performance of the JRCS is characterized by data throughput related to the radar echo data (RED) and communication data rate (CDR). Two spectral coexistence schemes are proposed based on the degree of spectrum sharing for radar and communication, i.e., the isolated subfrequency band (ISFB) and mix-used frequency band (MUFB) schemes. Firstly, the signals of radar and communication are operated on the isolated subcarriers, enabling the received signals to be processed independently and bringing the advantage of interference avoidance. Secondly, the signals of radar and communication can be jointly operated on the same subcarriers for the MUFB scheme, which enhances the spectrum efficiency. Unlike the ISFB scheme, the CDR of the MUFB scheme is maximized along with the interference from the radar signal, and meanwhile, the allocated radar power on each subcarrier is derived by maximizing the radar mutual information. Numerical results show that the MUFB scheme significantly improves the performance of data transmission over the ISFB scheme, and a significant performance gain in the data transmission can be achieved, compared to the average power allocation case.

A Method for Designing Low Peak to Average Power Cognitive Radar Waveform

2014 ◽  
Vol 716-717 ◽  
pp. 1055-1059
Author(s):  
Xue Mei Wang ◽  
Chun Yang Wang ◽  
Yu Chen ◽  
Yan Xin Yu ◽  
Hong Yan Sun
Keyword(s):  
Communication Systems ◽  
Average Power ◽  
Radar Signal ◽  
Transform Domain ◽  
Cognitive Radar ◽  
Complementary Sequence ◽  
Detection Range ◽  
Transmitter Power ◽  
Distant Target ◽  
Radar Echo

In this paper, the basis function of TDCS system (Transform Domain Communication System) is used to design cognitive radar transmitter waveform. Based on the noise environment, the waveform can be adjusted adaptively. Then after clipping to reduce the PAPR (Peak to Average Power Ratio) of radar echo signal, the obtained signal is used as the next launch of the radar signal. The cognitive radar transmitter requires a nonlinear waveform to improve the efficiency of radar transmitter power amplifier, so reducing the PAPR of signal is essential. This paper presents the gray complementary sequence is applied to TDCS communication systems, and then it needs to reduce PAPR of signals by clipping. Proven, PAPR of the transmitted signal is maintained at about 3.25dB, and the signal has a low probability of intercept, high anti-interference ability and distant target detection range.

scholarly journals Structural changes in lower ionosphere wind trends at midlatitudes

2010 ◽  
Vol 8 ◽  
pp. 231-236
Author(s):  
C. Jacobi ◽  
E. G. Merzlyakov ◽  
R. Q. Liu ◽  
T. V. Solovjova ◽  
Y. I. Portnyagin
Keyword(s):  
Structural Changes ◽  
Linear Trend ◽  
Piecewise Linear ◽  
A Priori ◽  
Lower Thermosphere ◽  
Lower Ionosphere ◽  
Lower Atmosphere ◽  
Data Series ◽  
E Region ◽  
Straight Lines

Abstract. Long-term variability of the mesosphere/lower thermosphere (lower E region ionosphere) since 1970 has been analyzed using wind data series obtained at Collm (52° N, 15° E) using the LF drift method and at Obninsk (55° N, 37° E) applying VHF meteor radar. Applying piecewise linear trend analysis with a priori unknown number and positions of breakpoints shows that trend models with breakpoints are generally to be preferred against straight lines. There is a strong indication for a change of trends in wind parameters around 1975–1980. Similar changes are also found in the lower atmosphere, e.g., in tropospheric temperatures. This indicates a coupling between atmospheric layers at time scales of decades.

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