A Residual Frequency Offset Estimation Method Based on Range Migration Fitting

Recently,researchers have proposed an emitter localization method based on passive synthetic aperture.However,the unknown residual frequency offset(RFO)between the transmit-ter and the receiver causes the received Doppler signal to shift,which affects the localization accu-racy.To solve this issue,this paper proposes a RFO estimation method based on range migration fitting.Due to the high frequency modulation slope of the linear frequency modulation(LFM)-mod-ulation radar signal,it is not affected by RFO in range compression.Therefore,the azimuth time can be estimated by fitting the peak value position of the pulse compression in range direction.Then,the matched filters are designed under different RFOs.When the zero-Doppler time obtained by the matched filters is consistent with the estimated azimuth time,the given RFO is the real RFO between the transceivers.The simulation results show that the estimation error of azimuth distance does not exceed 20 m when the received signal duration is not less than 3 s,the pulse repe-tition frequency(PRF)of the transmitter radar signal is not less than 1 kHz,the range detection is not larger than 1000 km,and the signal noise ratio(SNR)is not less than-5 dB.

LFM Radar Source Passive Localization Algorithm Based on Range Migration

Traditional single-satellite passive localization algorithms are influenced by frequency and angle measurement accuracies,resulting in error estimation of emitter position on the order of kilometers.Subsequently,a single-satellite localization algorithm based on passive synthetic aper-ture(PSA)was introduced,enabling high-precision positioning.However,its estimation of azimuth and range distance is considerably affected by the residual frequency offset(RFO)of uncoopera-tive system transceivers.Furthermore,it requires data containing a satellite flying over the radia-tion source for RFO search.After estimating the RFO,an accurate estimation of azimuth and range distance can be carried out,which is difficult to achieve in practical situations.An LFM radar source passive localization algorithm based on range migration is proposed to address the dif-ficulty in estimating frequency offset.The algorithm first provides a rough estimate of the pulse repetition time(PRT).It processes intercepted signals through range compression,range interpola-tion,and polynomial fitting to obtain range migration observations.Subsequently,it uses the changing information of range migration and an accurate PRT to formulate a system of nonlinear equations,obtaining the emitter position and a more accurate PRT through a two-step localization algorithm.Frequency offset only induces a fixed offset in range migration,which does not affect the changing information.This algorithm can also achieve high-precision localization in squint scenar-ios.Finally,the effectiveness of this algorithm is verified through simulations.

An integrated front-end vertical hall magnetic sensor fabricated in 0.18μm low-voltage CMOS technology

An integrated front-end vertical CMOS Hall magnetic sensor is proposed for the in-plane magnetic field measure-ment.To improve the magnetic sensitivity and to obtain low offset,a fully symmetric vertical Hall device(FSVHD)has been op-timized with a minimum size design.A new four-phase spinning current modulation associated with a correlated double sampling(CDS)demodulation technique has been further applied to compensate for the offset and also to provide a linear Hall output voltage.The vertical Hall sensor chip has been manufactured in a 0.18μm low-voltage CMOS technology and it occu-pies an area of 1.54 mm2.The experimental results show in the magnetic field range from-200 to 200 mT,the entire vertical Hall sensor performs with the linearity of 99.9%and the system magnetic sensitivity of 1.22 V/T and the residual offset of 60μT.Meanwhile,it consumes 4.5 mW at a 3.3 V supply voltage.The proposed vertical Hall sensor is very suitable for the low-cost sys-tem-on-chip(SOC)implementation of 2D or 3D magnetic microsystems.