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Focus FMCW SAR Data Using the wavenumber domain algorithms

Focus FMCW SAR Data Using the

Wavenumber Domain Algorithm

Robert Wang,Member,IEEE,Otmar Loffeld,Senior Member,IEEE,Holger Nies,Stefan Knedlik,Member,IEEE,

Manfred H?gelen,and Helmut Essen

Abstract—The combination of frequency-modulation continuous-wave(FMCW)technology and synthetic aperture radar(SAR)promises a lightweight,cost-effective,and high-quality imaging sensor for remote sensing.However,the long signal duration time leads to the failure of the conventional start/stop approximation of the pulsed SAR.In this paper,a signal model is proposed to address the effects of the continuous motion during the transmit time on the echoed signal.Based on the model,an analytical point target reference spectrum is derived.From the spectrum,it will be seen that the continuous motion introduces an additional range–azimuth coupling term and a range walk term compared with the conventional pulsed SAR.The range walk term is well known,whereas the foregoing range–azimuth coupling term is formulated for the?rst time in the FMCW SAR community.For the squint and spotlight modes,these range walk and range–azimuth coupling terms might signi?cantly degrade the image quality.In this paper,based on the proposed analytical signal model,we further discuss the application of the wavenumber domain algorithm for the FMCW SAR data.In addition,different approximations of the Stolt mapping are made to highlight the effect of the range-dependent higher-order range–azimuth coupling terms on the2-D impulse responses.Finally,X-band simulated experiments and Ka-band real FMCW SAR data are used to validate the signal model and the processing method.

Index Terms—Frequency-modulation continuous wave (FMCW),point target reference spectrum(PTRS),range cell migration correction(RCMC),wavenumber domain algorithm (WDA).

I.I NTRODUCTION

C ONVENTIONAL synthetic aperture radar(SAR)works

in pulsed mode[1].Continuous-wave technology,how-ever,requires less peak transmit power[2],[3].Hence, frequency-modulation continuous-wave(FMCW)SAR offers the bene?ts of compact size and low cost.However,it is currently applied only in the short-range case.

For FMCW SAR,the variation of the instantaneous slant range introduced by the continuous motion during the pulse time is no longer negligible since the conventional start/stop approximation does not hold.Conceptually,this start/stop ap-

Manuscript received May12,2009;revised July5,2009and July27,2009. First published November24,2009;current version published March24,2010. R.Wang,O.Loffeld,H.Nies,and S.Knedlik are with the Center for Sensorsystems(ZESS),University of Siegen,57076Siegen,Germany (e-mail:wang@zess.uni-siegen.de;loffeld@zess.uni-siegen.de;nies@zess. uni-siegen.de;knedlik@zess.uni-siegen.de).

M.H?gelen and H.Essen are with the Fraunhofer Institute for High Fre-quency Physics and Radar Techniques(FHR),53343Wachtberg,Germany (e-mail:m.haegelen@fgan.de;essen@fgan.de).

Color versions of one or more of the?gures in this paper are available online at https://www.wendangku.net/doc/161176445.html,.

Digital Object Identi?er10.1109/TGRS.2009.2034368proximation assumes that any transmitted pulse experiences a delay time,which is constant during the pulse duration and only varies from pulse to pulse(known as range migration),whereas in principle,leading edge and trailing edge of any transmitted pulse experience different delay times introduced by the time-varying slant range.Therefore,processing of FMCW SAR differs from the conventional pulsed SAR due to the fact that the range walk term and an additional range–azimuth coupling are introduced by the continuous motion of the antenna while transmitting and receiving the signal.The range walk term is discussed in detail in[3],whereas the additional range–azimuth coupling term is not mentioned.Therefore,conventional SAR algorithms cannot directly be applied.Recently,several con-ventional algorithms have been modi?ed to focus FMCW SAR data[3]–[7].The range-Doppler algorithm has been modi?ed to focus FMCW SAR data in[4].In[4],the continuous motion within the sweep is discussed and compensated by modifying the range migration compensation.Meta et al.[5]present a nonlinear frequency-scaling algorithm,which simultaneously performs the nonlinear correction,Doppler-shift correction,and range cell migration correction(RCMC)in the wavenumber domain.It can be considered as an extension of the result proposed in[6].In addition,a chirp transformation algorithm is also used to process FMCW SAR data[7].The aforementioned three methods neglect the range-dependent second-and higher-order range–azimuth coupling terms that play a key role in the squint or spotlight modes.

In this paper,we begin with a signal model,which accurately represents the effect of the variation of the instantaneous slant range during the pulse time on the transmitted and echoed signal.This variation during the transmitting time introduces a range-invariant range walk and a range–azimuth coupling. The range walk is corrected by a phase multiplication,which can be incorporated into the reference function multiplication (RFM)[9].RFM is applied in the2-D frequency domain.It works as a bulk compressor[9]and is responsible for the range-independent range walk,high-order range frequency terms,and azimuth compression.After RFM,we perform the Stolt inter-polation in the wavenumber domain[8],[9].The Stolt inter-polation can correct the range-dependent RCM and cancel the range-dependent higher-order range–azimuth coupling terms and azimuth modulation.Therefore,it is suitable to process the FMCW SAR in the spotlight and high-squint modes.To demon-strate the performance of the wavenumber domain algorithm (WDA),the different approximations of the Stolt mapping are used to highlight the effect of the range-dependent higher-order range–azimuth coupling components on2-D focusing.In this paper,our processing procedure proceeds with the removal of

0196-2892/$26.00?2009IEEE

Fig.1.Geometry of the SAR system.

the residual video phase(RVP),which is introduced by the applied dechirp-on-receive operation.The compensation of the RVP has been discussed in detail in[10]and[11].

This paper is organized as follows.In Section II,the signal model and the point target reference spectrum(PTRS)are derived.Section III begins with the spectrum and uses the WDA for processing FMCW SAR data.Hereafter,we show the processing results of simulated raw data in Section IV and of real FMCW SAR data in Section V.Finally,conclusions are reported in Section VI.

II.S IGNAL M ODEL AND PTRS

In this paper,we consider the general SAR geometry,as shown in Fig.1.

The mathematical symbols and their de?nitions used in this paper are given as follows.

τ,t Azimuth and range time variables.

r0Closest ranges from the antenna to the target P(τ0,r0).

r c Reference slant range for the dechirp-on-receive approach.

τ0Zero-Doppler time of the target P(τ0,r0).

σ(τ0,r0)Backscattering coef?cient of the point target P(τ0,r0).

r m Closest range from the scene center to the?ight trajectory.

λ,f0Carrier wavelength and carrier frequency of the transmitted signal.

c Spee

d of light.

f,fτRange and azimuth frequency variables.

K r Chirp rate of the transmitted signal.

T p Pulse repetition period.

In the pulsed SAR,the start/stop approximation is commonly used,where the instantaneous slant range from the antenna to the target is assumed to remain constant during the pulse time. In the case of the continuous-wave(CW)SAR,however,the instantaneous slant range can no longer be assumed constant due to the long signal duration.To develop the signal model for the CW SAR system,we?rst perform an analysis of the round-trip delay time.Let the timeτd be the round-trip delay time for the wave propagation.The signal is transmitted at an arbitrary timeτat an instantaneous slant range R(τ)and arrives back at the receiver at timeτ+τd,having traveled along the slant range from the target to the receiver R(τ+τd).Thus,we can express the round-way delay time as

R(τ+τd)+R(τ)

c

=τd(1) where

R(τ)=

r20+v2(τ?τ0)2(2) R(τ+τd)=

r20+v2(τ+τd?τ0)2.(3)

Shifting R(τ)/c to the right-hand side and squaring both sides,we can obtain a quadratic equation in terms ofτd.By solving the quadratic equation forτd,we obtain

τd=2α

R(τ)

c

+

v2

c2

(τ?τ0)

(4) where the“Doppler factor”αis de?ned as

α=

1

1?v2

c2

.(5)

By using(4),and neglecting the timescaling in?uences on the pulse envelope,the echoed signal can be expressed as

g r(τ,t,r0,s0)=σ(τ0,r0)s l(t?τd)exp[j2πf0(t?τd)](6)

where s l(t)represents the transmitted FM signal,which is de?ned as s l(t)=exp(jπK r t2).Since the SAR is time co-herent,the transmitted signal is synchronized by the repetition period,i.e.,t=τ?nT p.The signal is transmitted at the time τn=nT p,where n denotes the period number.

In the pulsed mode,the pulse duration is short on the order of a few microseconds;however,for the FMCW mode,the pulse duration is on the order of milliseconds,corresponding to the pulse repetition interval.The dechirp-on-receive technology is generally used in the FMCW SAR system to reduce the sampling requirements and data rate[3],[10].The reference signal for dechirp processing is de?ned as

g ref(τ,t,t c)=s?l(t?τc)exp[?j2πf0(t?τc)](7)

where s?

l

(t)denotes the conjugate of the transmitted signal s l(t),andτc is the time delay of the reference signal.For nota-tional convenience,τc is de?ned asτc=2αr c/c.The dechirped signal can be expressed as

g IF(τ,t,r0,τ0)=g(τ,t,r0,τ0)×g ref(τ,t,t c)

=σ(τ0,r0)exp[?j2πf0(τd?τc)]

×exp[?j2πK r(τd?τc)(t?τc)]

×exp

?j2πK r(τd?τc)2

.(8)

The last exponential term of(8)is well known as an RVP [10].Removing the RVP needs Fourier transformation(FT), phase multiplication,and inverse FT(IFT)[10],[11].The

WANG et al.:FOCUS FMCW SAR DATA USING THE WAVENUMBER DOMAIN ALGORITHM 2111

following derivation assumes that the RVP has been removed,i.e.,

g IF (τ,t,r 0,τ0)=σ(τ0,r 0)exp [?j 2πf 0(τd ?τc )]

×exp [?j 2πK r (τd ?τc )(t ?τc )].(9)

Performing the time–frequency substitution of K r (t ?τc )→f yields

g IF (τ,f,r 0,τ0)=σ(τ0,r 0)×exp [?j 2π(f 0+f )(τd ?τc )].

(10)To segment the received signal into the 2-D discrete domain,we substitute τ=τn +t into (10).Equation (10)can then be reformulated as g IF (τn ,t,f,r 0,τ0)

=σ(τ0,r 0)

exp

?j 4πα(f 0+f )

×

R (τn +t )c +v 2c 2(τn +t ?τ0)?

r c c

.(11)

To obtain the PTRS,we apply the FT to (11)with respect to

the discrete-time variable τn ,i.e.,

G IF (f τ,t,f,r 0,τ0)=

g IF (τn ,f,r 0,τ0)

×exp[?j 2πf ττn ]dτn =σ(τ0,r 0)

exp [?j Φ(f τ,f,τn )]dτn

(12)

where Φ(f τ,f,τn )is de?ned as

Φ(f τ,t,f,τn )=4πα(f 0+f )

× R (τn +t )c +v 2c 2(τn +t ?τ0)?r c c +2πf ττn .(13)

Consequently,the principle of stationary phase can readily be

applied to obtain the solution of the integral to derive the desired PTRS.At the point of stationary phase,the ?rst derivative of the phase Φ(f τ,f,τn )is zero,i.e.,

d Φ(f τ,t,f,τn )dτn

τn =τp

=0.(14)Solving (14)for τp yields

τp =τ0?r 0v

v c

+

cf τ

2αv (f 0+f )

1?

v c

+

cf τ

2αv (f 0+f )

2?t.

(15)

Substituting τp on the right-hand side of (12)for τn gives the desired PTRS (The nonessential amplitude and phase terms are disregarded.).Thus

G IF (f τ,f,r 0,s 0)=σ(τ0,r 0)exp [?j Φ(f τ,f,r 0)]

(16)

Fig.2.Block diagram of the focusing algorithm.

where the phase term in the 2-D frequency domain can be expressed as (note that the substitution K r (t ?τc )→f is further introduced)

Φ(f τ,f,r 0)=

4παr 0

c

(f 0+f )2?

v c (f 0+f )+cf τ2αv

2

?2πf τ

f K r +2πf ττ0?4πα(f 0+f )r c

c ?4απr c c

f τ.(17)

Some short remarks concerning (17)will be helpful to under-stand the characteristics of this FMCW SAR.

1)The square root contains the additional term (v/c )(f 0+f ),which is not presented in the pulsed SAR PTRS [9].It adds a range–azimuth coupling in the 2-D fre-quency domain,which results in the skewness of the 2-D spectrum along the range frequency direction [9].It is introduced by the variation of the slant range during the long pulse duration.This coupling term is the basic difference between this proposed spectrum and the one presented in [3],where it is neglected.

2)The second term in (17)(i.e.,?2π(f τ/K r )f )is a range-invariant range walk term,which is also caused by the variation of the slant range during the pulse duration.3)2πf ττ0is linearly dependent on the zero-Doppler time of the target and thus determines the azimuth registration position of the target after azimuth compression.The last two terms,i.e.,4πα(f 0+f )(r c /c )and 2πf τ(2r c /c ),refer to the constant range and azimuth shifts,respectively,and are introduced by the dechirp-on-receive approach.They can be removed by using RFM.

III.P ROCESSING P ROCEDURE

This section provides the processing steps of the proposed algorithm shown in Fig.2and illustrates its basic operation.

2112IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,VOL.48,NO.4,APRIL 2010

The basic steps are outlined in the list that follows.

1)Remove RVP.This operation requires the range FT,chirp phase multiplication,and range IFT.It is described in detail in [10]and [11].

2)Perform the FT in the azimuth to transform the raw data into the 2-D frequency domain.

3)RFM.It is carried out to remove the range-invariant phase (i.e.,bulk range walk,constant azimuth shift,az-imuth modulation,bulk RCM,and bulk secondary range compression (SRC)[9]).Thus,the RFM ?lter can be expressed as

H RFM (f τ,f,r ref )=exp [j ΦR (f τ,f,r ref )]

(18)

where ΦR (f τ,f,r ref )is de?ned as

ΦR (f τ,f,r ref )=4παr ref c (f 0+f )2? v c (f 0+f )+

cf τ

2αv

2

?2πf τf K r ?4πα(f 0+f )r c

c ?4απr c c

f τ

(19)

where r ref denotes the reference range for focus process-ing,which is generally de?ned as the closest slant range from the scene center to the receiver.Via RFM ?ltering,the targets at the reference range are correctly focused,but the targets away from the range are only partially focused [9].After RFM ?ltering,the remaining signal becomes

G 1(f τ,f,r 0,τ0)=G IF (f τ,f,r 0,τ0)×H RFM (f τ,f,r ref )

=σ(τ0,r 0)exp [?j ΦRFM (f τ,f,r 0)]

(20)

where ΦRFM (f τ,f,r 0)is formulated as ΦRFM (f τ,f,r 0)=

4πα(r 0?r ref )

c ×

(f 0+f )2? v c (f 0+f )+cf τ2αv

2?2πf ττ0.(21)

From (21),it can be seen that the range walk caused by

the continuous motion is removed by RFM.

4)Perform the Stolt interpolation.After removing the range walk,the conventional WDA can directly be applied to focus FMCW SAR data.For the WDA,the Stolt interpolation needs to be performed to remap the range frequency variable and is formulated as (f 0+f )2? v c (f 0+f )+cf τ2αv 2

→f 0+f 1.(22)For the traditional pulsed SAR processing,the Stolt inter-polation is de?ned as [9]

(f 0+f )2? cf τ

2v 2

→f 0+f 1.(23)

Therefore,the additional range–azimuth coupling term in the Stolt variable is the essential difference between

the traditional pulsed SAR and the FMCW SAR.In [12],another Stolt interpolation is presented,which is given as

α(f +f 0)2?1α v c (f +f 0)?cf τ2αv 2→f 0+f 1.(24)The Stolt variable involved in (24)is derived based on the

assumption that the time from the transmitter to the target is equal to half of the round-trip delay.In fact,as stated in the footnote of [12],it is an approximation,whereas (22)is obtained based on the analytical derivations shown in (1)–(4).After the remapping transformation,the resulting phase is now linearly dependent on the new range fre-quency variable f 1,i.e.,

ΦStolt (f τ,f,r 0)=?

4πα(r 0?r ref )

c

(f 0+f 1)?2πf ττ0.

(25)

From (25),we can ?nd that the Stolt interpolation com-pletely removes the range–azimuth coupling and azimuth

modulation.

5)Transform the signal into the complex image domain by performing the 2-D IFT.We obtain

g 1(τ,t,τ0,r 0)=p r t ?

2α(r 0?r ref )

c

p a (τ?τ0)(26)where p r (t )and p a (τ)are the compressed pulse envelope in the range and the azimuth,respectively.

From (22),it can be seen that no approximations have been performed for the RCMC and SRC.Hence,it has an advantage of precisely correcting the range-dependent second-and higher-order range–azimuth coupling terms,regardless of the squint or the aperture width.

The range-dependent second-and higher-order range–azimuth coupling terms not only result in the range focusing degradation but also defocus the azimuth impulse response since they also contain azimuth modulation components.The involved azimuth modulation components can be understood by expanding (21)using a Taylor series,i.e.,ΦRFM (f τ,f,r 0)≈

4πα(r 0?r ref )

c ×

Df 0+

(1?μ1μ2)D f ?(μ1?μ2)22f 0D 3

f 2+(μ1?μ2)2(1?μ1μ2)2f 20

D 5f 3+···

?2πf ττ0(27)where D denotes the cosine of the instantaneous squint angle in the Doppler domain and is de?ned as

D =

1?μ21.(28)The parameters μ1and μ2are formulated as

μ1=

v

c +cf τ2αv

μ2=

v

c

.(29)

WANG et al.:FOCUS FMCW SAR DATA USING THE WAVENUMBER DOMAIN ALGORITHM

2113

Fig.3.Scene geometry with three point targets.Target PT2is located in the scene center.PT1and PT3have the relative slant ranges:?150and 150m,respectively,with respect to PT2.

TABLE I

S YSTEM P

ARAMETERS

For the methods in [4],[5],and [7],the effect of the second-and higher-order terms are neglected.It means that (27)is terminated after the ?rst-order term and is given as ΦRFM (f τ,f,r 0)≈

4πα(r 0?r ref )

c × Df 0+(1?μ1μ2)

D

f

?2πf ττ0.(30)

The approximation involved in (30)can be considered as their limitation.In the following section,we will highlight the limitation using a simulation experiment.

IV .S IMULATION E XPERIMENT

In this section,an airborne simulation is carried out to validate the performance of the present methods and analyze the effect of the higher-order range–azimuth coupling terms.To highlight the range dependence of the PTRS and the focusing capacity of the WDA,the designed scene consists of three point targets orthogonal to the ?ight direction,as shown in Fig.3.The system parameters are listed in Table I.

In this experiment,different broadside and squint con?gu-rations are simulated to highlight the role of the higher-order range–azimuth coupling terms.To quantify the precision of processing,the impulse response width (IRW),peak sidelobe ratio (PSLR),and integrated sidelobe ratio (ISLR)are used as criteria.For the ongoing simulation,we assume the window function of rectangular shape in both directions.

A.Broadside Con?guration

In the broadside con?guration,the ideal IRW is 0.3m in range and 0.343m in azimuth.In the following,we perform the two kinds of Stolt interpolation transformation.

1)Case 1:an approximated interpolation neglecting the second-and higher-order coupling terms,i.e.,

Df 0+

(1?μ1μ2)

D f →f 0+f 1.(31)2)Case 2:the Stolt interpolation described by (22).

1)Case 1:The ?rst interpolation transformation is based on the approximation of (30),which neglects the second-and higher-order coupling terms.The resulting phase error can be expressed as ΦE (f τ,f,r 0)≈

4πα(r 0?r ref )

c ×

(f 0+f )2?

v c (f 0+f )+cf τ2αv

2

?Df 0?

(1?μ1μ2)

D

f

.(32)The focused result using the transformation of (31)is shown in Fig.4(a).

To examine the focusing performance in more detail,the point target PT3is highlighted,and the contour of the target energy is shown in Fig.4(b).From Fig.4(b),it can be seen that the 2-D measured parameters agree well with the theoretical values,which means that the ignored second-and higher-order phase-coupling terms do not seriously degrade the focusing performance.This phenomenon can be explained using the ap-proximation phase error term (32),which is shown in Fig.4(c).From Fig.4(c),we can ?nd that the maximum of the phase error is less than 0.1π,i.e.,|ΦE |<0.1π,which satis?es an ac-ceptable level of π/4[9].Therefore,in this case,it is reasonable to neglect the second-and higher-order terms in (31).This is also the right reason that the preceding three methods (i.e.,[4],[5],and [7])achieve satisfactory focusing results.

2)Case 2:This interpolation transformation is the original Stolt interpolation [8],[9].The resulting focusing result is shown in Fig.4(d).To observe more clearly,the 2-D impulse response of PT3is shown in Fig.4(e).

From Fig.4(e),it can be seen that the WDA also focuses the simulated scene well in the broadside https://www.wendangku.net/doc/161176445.html,paring Fig.4(b)and (e),we may note that the second-and high-order range–azimuth coupling components almost have no effect on the 2-D impulse response in the broadside case.B.High-Squint Con?guration

In the squint con?guration of 40?,the ideal IRW is 0.3m in range and 0.4485m in azimuth.We use three interpola-tion transformations to demonstrate the performance of the WDA and highlight the role of the second-and higher-order range–azimuth coupling terms.

2114IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,VOL.48,NO.4,APRIL

2010

Fig.4.(a)Focused scene processed using the interpolation transformation of(18)in the broadside con?guration.(b)Impulse responses of target PT3.

(c)Approximation phase error of PT3in the broadside con?guration.(d)Focused scene processed using the interpolation transformation of(18)in the broadside con?guration.(e)Impulse responses of target PT3.

1)Case1:the?rst-order polynomial interpolation transfor-

mation,i.e.,(31).

2)Case2:the Stolt interpolation,i.e.,(22).

3)Case3:the third-order polynomial interpolation transfor-

mation,i.e.,

Df0+(1?μ1μ2)

D

f?

(μ1?μ2)2

2f0D3

f2

+

(μ1?μ2)2(1?μ1μ2)

2f20D

f3

→f0+f1.(33)

1)Case1:First,we show the focusing result by using(31) in Fig.5(a).

From Fig.5(a),it can be seen that the targets away from

the swath center considerably degrade in both directions.The

degradations imply that the neglected range–azimuth coupling

components have a signi?cant effect on the2-D impulse re-

sponses.To clearly identify the effect of the phase error,we

show the approximation phase error of PT3in Fig.5(b).

Fig.5(b)shows that the maximum of the approximation

phase error|ΦE|is greater than10π,which is much more than the acceptable level ofπ/4[9].It is caused by the neglected

higher-order range–azimuth coupling components.

The methods proposed in[4],[5],and[7]are originally de-

signed for swath SAR zero-Doppler processing and thus neglect

higher-order range–azimuth coupling components.Apparently,

WANG et al.:FOCUS FMCW SAR DATA USING THE WAVENUMBER DOMAIN ALGORITHM2115

Fig.5.(a)Focused scene by using the?rst-order polynomial interpolation transformation.(b)Approximation phase error of the?rst-order polynomial interpolation transformation in the squint con?guration.(c)Focused scene processed using the interpolation transformation of(13)in the squint con?guration.

(d)Impulse responses of target PT3.(e)Focused scene processed using the interpolation transformation of(20)in the squint con?guration.(f)Impulse responses of target PT3.(g)Approximation phase errorˉΦE3(f a,f)of PT3in the squint con?guration.(h)Approximation phase errorˉΦE2(f a,f)of PT3in the squint con?guration.

2116IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,VOL.48,NO.4,APRIL2010 they are not suitable to process FMCW SAR data in the high-

squint case.

2)Case2:The focused result by using(22)is shown in

Fig.5(c).For clarity,PT3is zoomed and shown in Fig.5(d).

From the measured parameters shown in Fig.5(d),IRW

broadening is1.67%in range and0.84%in azimuth;the degra-

dation in the ISLR is less than0.3dB in both directions;and

the PSLR agrees well with the theoretical value,which means

that the WDA works well in the squint con?guration.

3)Case3:This case is to further validate the role of the

higher-order phase terms.The phase error introduced by(33)is

de?ned as

ˉΦE3(fτ,f,r0)≈

4πα(r0?r ref)

c

×

(f0+f)2?

v

c

(f0+f)+

cfτ

2αv

2

?Df0?(1?μ1μ2)

D

f+

(μ1?μ2)2

2f0D3

f2

?(μ1

?μ2)2(1?μ1μ2)

2f20D5

f3

.(34)

The focused scene is shown in Fig.5(e).In addition,the zoomed impulse response of PT3is given in Fig.5(f).

Comparing this with the results shown in Fig.5(d),only the range impulse response has little degradation.The range IRW deteriorates with a broadening of3%,and the range PSLR has a deviation of less than0.1dB compared with the theo-retical values.Therefore,we conclude that the result with the transformation(33)approximately agrees with the ideal one, which implies that the second-and third-order components play a signi?cant role in the high-squint con?guration.For further clarity,we show the approximation phase errorˉΦE3(fτ,f)of PT3in Fig.5(g).

From Fig.5(g),it can be seen that the approximation error ˉΦ

E3

(fτ,f)is https://www.wendangku.net/doc/161176445.html,paring Fig.5(b)and(g),it can be seen that the second-and third-order range–azimuth coupling components play a key role in the high-squint con?guration. Neglecting them might result in considerable focusing degra-dation in both directions.

To further highlight the role of the third-order term,the phase error of the second-order polynomial interpolation transforma-tion is shown in Fig.5(h).The phase error function for the second-order polynomial is formulated as

ˉΦE2(fτ,f,r0)≈

4πα(r0?r ref)

c

×

(f0+f)2?

v

c

(f0+f)+

cfτ

2αv

2

?Df0?(1?μ1μ2)

D

f+

(μ1?μ2)2

2f0D3

f2

.

(35)

Fig.6.(a)SAR image processed by the presented algorithm.(b)Optical

image from Google Earth.The processed image has a size of331m(slant

range)×897m(azimuth)at Herrenchiemsee,Germany.The horizontal and

vertical directions denote the range and the azimuth,respectively.

From Fig.5(h),it can seen that the phase error in the

second-order model is greater than the acceptable level ofπ/4.

Therefore,the third-order term in(33)is necessary for this40?

squint case.

V.P ROCESSING R ESULT OF R EAL FMCW SAR D ATA

In this section,the signal model and the processing method

are validated by real Ka-band FMCW SAR data,which are

acquired by using FHR’s airborne millimeter-wave SAR system

(i.e.,MEMPHIS)[13],[14],in April2008.MEMPHIS is a

unique experimental millimeter-wave SAR system that contains

two front ends:one operates at35GHz(Ka-band)and another

at94GHz(W-band).The radar system is mounted on a Transall

C-160aircraft with a?ight altitude of320m,a velocity of

75m/s,and a looking angle of70?.For this?ight campaign,

the minimum slant range is600m,and the maximum range

is1000m.The system has a range bandwidth of2GHz and

an azimuth Doppler bandwidth of295Hz.The corresponding

range resolution is0.075m,and the azimuth resolution is

0.25m.It needs to emphasize that a sampling frequency of

25MHz is applied in the range since the dechirp-on-receive

technology is used.

To obtain accurate focusing,the onboard Inertial Navigation

System and Global Positioning System are used to collect the

information of the position and attitude of the antenna phase

center.For this processing,we only implement the range-

invariant correction,i.e.,the correction for the reference slant

WANG et al.:FOCUS FMCW SAR DATA USING THE WAVENUMBER DOMAIN ALGORITHM2117

range[11],[15]–[17].In this paper,we choose the slant range at the middle swath as the reference slant range.Since our real data have a short swath of400m,and thus the range-invariant component(i.e.,at the reference slant range)is dominant,we neglect the range-variant component for our processing.

By using the proposed signal model and imaging algorithm, the focused SAR image is shown in Fig.6(a).For comparison, the optical image of the processed scene is shown in Fig.6(b). The real Ka-band data are acquired in approximately the broadside case(yaw angle:2.44?).Therefore,for these real data,the suggested WDA processing does not demonstrate the improved performance since the previous algorithms(i.e., [4],[5],and[7])can also work well in the broadside case [see Fig.4(c)].

VI.C ONCLUSION

In this paper,we have developed a signal model for the FMCW SAR to address the range variation during the long pulse duration,which is different from the pulsed SAR.Based on the signal model,an analytical PTRS has been developed. Compared with the PTRS of the pulsed SAR,an additional range walk term and a range–azimuth coupling term are found. The range–azimuth coupling term has been disregarded so far in the FMCW SAR community.After RFM to remove the range walk,we use the WDA to focus FMCW SAR data. Simulation experiments show that the WDA can focus FMCW SAR data well in the broadside and high-squint cases.In the high-squint case,it does not require additional computational burden compared with the broadside case.It needs to emphasize that the previous algorithms in[4],[5],and[7]perform well in the broadside case but fail in high-squint cases.

In addition,three interpolation mapping transformations are used to emphasize the role of the range-dependent second-and higher-order range–azimuth coupling components in the high-squint case.Simulations also show that neglecting the higher-order phase terms will result in a signi?cant degradation in both directions.The processing result of the real data shows that the proposed signal model and the processing method can work well in the case of the millimeter-wave FMCW SAR.

A CKNOWLEDGMENT

The authors would like to point out the excellent and very ef-fective cooperation between ZESS and Fraunhofer/FHR,which is seen as a key item of this paper.Finally,the authors would like to thank the anonymous reviewers for their competent and helpful suggestions to improve this paper.

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2006.

Robert Wang(M’07)received the B.S.degree in

control engineering from the University of Henan,

Kaifeng,China,in2002and the Dr.Eng.degree from

the Graduate University of the Chinese Academy of

Sciences,Beijing,China,in2007.

In2007,he joined the Center for Sensorsystems

(ZESS),University of Siegen,Siegen,Germany,

where he is currently working on the hybrid bistatic

experiment.He was also involved in some SAR

projects for the Fraunhofer Institute for High Fre-

quency Physics and Radar Techniques(FHR).He has contributed to invited sessions on bistatic SAR at the European Conference on Synthetic Aperture Radar(EUSAR)2008.He is the author of a tutorial entitled “Results and progresses of advanced bistatic SAR experiments”presented at the European Radar Conference2009and the coauthor of a tutorial entitled “Progress in bistatic SAR concepts and algorithms”presented at EUSAR 2008.His current research interests include monostatic and bistatic SAR signal processing,bistatic interferometric,airborne SAR motion compensation, FMCW SAR systems,and millimeter-wave SAR systems.

2118IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,VOL.48,NO.4,APRIL

2010

Otmar Loffeld(M’05–SM’06)received the

Diploma degree in electrical engineering from

the Technical University of Aachen,Aachen,

Germany,in1982and the Eng.Dr.degree and the

“Habilitation”degree in the?eld of digital signal

processing and estimation theory from the University

of Siegen,Siegen,Germany,in1986and1989,

respectively.

In1991,he was appointed Professor of digital

signal processing and estimation theory with the

University of Siegen.Since then,he has been giving lectures on general communication theory,digital signal processing,stochastic models and estimation theory,and synthetic aperture radar.He is the author of two textbooks on estimation theory.In1995,he became a member of the Center for Sensorsystems(ZESS),which is a central scienti?c research establishment at the University of Siegen.Since2005,he has been the Chairman of ZESS. In1999,he became a Principal Investigator(PI)on baseline estimation for the X-band part of the Shuttle Radar Topography Mission(SRTM),where ZESS contributed to the German Aerospace Center(DLR)’s baseline cali-bration algorithms.He is a PI for interferometric techniques in the German TerraSAR-X mission,and,together with Prof.Ender from FGAN,he is one the PIs for a bistatic spaceborne airborne experiment,where TerraSAR-X serves as the bistatic illuminator,whereas the Fraunhofer Institute for High Frequency Physics and Radar Techniques(FHR)’s PAMIR system mounted on a Transall airplane is used as a bistatic receiver.In2002,he founded the International Postgraduate Programme(IPP)“Multi Sensorics.”In2008,based on the aforementioned program,he established the“NRW Research School on Multi Modal Sensor Systems for Environmental Exploration and Safety (MOSES)”at the University of Siegen as an upgrade of excellence.He is the Speaker and Coordinator of both doctoral degree programs,which are hosted by ZESS.Furthermore,he is the university’s Scienti?c Coordinator for“Multidimensional and Imaging Systems.”His current research interests comprise multisensor data fusion,Kalman?ltering techniques for data fusion, optimal?ltering and process identi?cation,SAR processing and simulation, SAR interferometry,phase unwrapping,and baseline estimation.His recent ?eld of interest is bistatic SAR processing.

Dr.Loffeld is a member of the Information Technology Society(ITG)of the German Association for Electrical,Electronic and Information Technologies (VDE)and a Senior Member of the IEEE Geoscience and Remote Sensing Society.He was the recipient of the Scienti?c Research Award of North Rhine-Westphalia(“Bennigsen-Foerder Preis”)for his works on applying Kalman ?lters to phase estimation problems such as Doppler centroid estimation in

SAR,phase,and frequency

demodulation.

Holger Nies received the Diploma degree in elec-

trical engineering and the Dr.Eng.degree from the

University of Siegen,Siegen,Germany,in1999and

2006,respectively.

Since1999,he has been a member of the Center

for Sensorsystems(ZESS),University of Siegen,and

a Lecturer with the Department of Signal Process-

ing and Communication Theory.He worked in the

project sector“Optimal Signal Processing,Remote

Sensing—SAR”of ZESS in1999.He was also

involved in some project work for Daimler AG, Stuttgart,Germany,in the?eld of engine modeling and optimization.He is currently working in the area of interferometric techniques in the German TerraSAR-X mission.He is a Principal Investigator on the development of a stationary receiver SAR system for acquiring and processing signals transmitted from the TerraSAR-X satellite.His current research interests include bistatic SAR processing,SAR interferometry,and distributed data fusion.

Dr.Nies was the recipient of the“Best Poster Award”at the European Conference on Synthetic Aperture Radar(EUSAR)2006,Dresden,

Germany.

Stefan Knedlik(M’04)received the Diploma degree

in electrical engineering and the Dr.Eng.degree

from the University of Siegen,Siegen,Germany,in

1998and2003,respectively.

Since1998,he has been a member of the Center

for Sensorsystems(ZESS),University of Siegen,and

since2003,he has also been a Researcher/Assistant

Professor(C1)with the Institute of Signal Processing

and Communication Theory,Department of Electri-

cal Engineering and Computer Science.He is also an

Executive Director of two international postgraduate programs:the International Postgraduate Programme(IPP)Multi Sensorics and the Research School on Multi Modal Sensor Systems for Environmental Exploration and Safety(MOSES).A few years ago,he founded a research group on navigation.His current research interests include GNSS-based navi-gation,inertial navigation,sensor data fusion,and signal processing in synthetic aperture radar

interferometry.

Manfred H?gelen received the Diploma degree in

electrical engineering from the Technical University

of Brunswick,Brunswick,Germany,in2003.He is

currently working toward the Ph.D.degree with the

International Postgraduate Programme Multi Sen-

sorics,Center for Sensor Systems(ZESS),Univer-

sity of Siegen,Siegen,Germany.

Since January2003,he has been a Research Asso-

ciate with the Fraunhofer Research Institute for High

Frequency Physics and Radar Techniques(FHR),

Wachtberg,Germany.In September2009,he be-came a Team Leader of Sensor Systems for Security Applications with the Department of Millimeter Wave Radar and High Frequency Sensors.His current research interests include multiple-sensor systems,FMCW SAR signal processing,airborne SAR motion compensation,FMCW SAR systems,and millimeter-wave radar

systems.

Helmut Essen received the Diploma degree in

physics and the Ph.D.degree from the Univer-

sity of Bonn,Bonn,Germany,in1973and1976,

respectively.

He was with the Max-Planck-Institute for radio-

astronomy,where he was engaged in the develop-

ment of millimeter-wave radiometers,until1977.

Since then,he has been with the Fraunhofer Re-

search Institute for High Frequency Physics and

Radar Techniques(FHR),Wachtberg,Germany,as a

Research Scientist and Group Leader,engaged in the development of millimeter-wave radar in the frequency range of10–220GHz. Since1995,he has been heading the Department of Millimeter Wave Radar and High Frequency Sensors.His work on target background signatures covered experimental investigations and the development of signal processing algo-rithms using SAR,InSAR,and ISAR.His further?elds of research have been propagation of radio waves and terahertz imaging for security applications. Dr.Essen is a member of the German Physical Society(DPG),the German Terahertz Center,and the IEEE Geoscience and Remote Sensing Society.

监控摄像机镜头的选择和主要参数

监控摄像机镜头的选择和主要参数 镜头相当于人眼的晶状体,如果没有晶状体,人眼看不到任何物体;如果没有镜头,那么摄像头所输出的图像就是白茫茫的一片,没有清晰的图像输出,这与我们家用摄像机和照相机的原理是一致的。当人眼的肌肉无法将晶状体拉伸至正常位置时,也就是人们常说的近视眼,眼前的景物就变得模糊不清;摄像头与镜头的配合也有类似现象,当图像变得不清楚时,可以调整摄像头的后焦点,改变CCD芯片与镜头基准面的距离(相当于调整人眼晶状体的位置),可以将模糊的图像变得清晰。由此可见,镜头在闭路监控系统中的作用是非常重要的。工程设计人员和施工人员都要经常与镜头打交道:设计人员要根据物距、成像大小计算镜头焦距,施工人员经常进行现场调试,其中一部分就是把镜头调整到最佳状态。 1、镜头的分类 按外形功能分按尺寸大小分按光圈分按变焦类型分按焦距长矩分 球面镜头1” 25mm 自动光圈电动变焦长焦距镜头 非球面镜头 1/2” 3mm 手动光圈手动变焦标准镜头 针孔镜头 1/3” 8.5mm 固定光圈固定焦距广角镜头 鱼眼镜头 2/3” 17mm (1)以镜头安装分类: 所有的摄象机镜头均是螺纹口的,CCD摄象机的镜头安装有两种工业标准,即C安装座和CS安装座。两者螺纹部分相同,但两者从镜头到感光表面的距离同。C安装座:从镜头安装基准面到焦点的距离是17.526mm。CS安装座:特种C安装,此时应将摄象机前部的垫圈取下再安装镜头。其镜头安装基准面到焦点的距离是12.5mm。如果要将一个C安装座镜头安装到一个CS安装座摄象机上时,则需要使用镜头转换器。 (2)以摄象机镜头规格分类: 摄象机镜头规格应视摄象机的CCD尺寸而定,两者应相对应。即摄象机的CCD靶面大小为1/2英寸时,镜头应选1/2英寸。摄象机的CCD靶面大小为1/3英寸时,镜头应选1/3英寸。摄象机的CCD靶面大小为1/4英寸时,镜头应选1/4英寸。如果镜头尺寸与摄象机CCD靶面尺寸不一致时,观察角度将不符合设计要求,或者发生画面在焦点以外等问题。 (3)以镜头光圈分类: 镜头有手动光圈(manual iris)和自动光圈(auto iris)之分,配合摄象机使用,手动光圈镜头适合于亮度不变的应用场合,自动光圈镜头因亮度变更时其光圈亦作自动调整,故适用亮度变化的场合。自动光圈镜头有两类:一类是将一个视频信号及电源从摄象机输送到透镜来控制镜头上的光圈,称为视频输入型,另一类则利用摄象机上的直流电压来直接控制光圈,称为DC输入型。自动光圈镜头上的ALC(自动镜头控制)调整用于设定测光系统,可以整个画面的平均亮度,也可以画面中最亮部分(峰值)来设定基准信号强度,供给自动光圈调整使用。一般而言,ALC已在出厂时经过设定,可不作调整,但是对于拍摄景物中包含有一个亮度极高的目标时,明亮目标物之影像可能会造成"白电平削波"现象,而使得全部屏幕变成白色,此时可以调节ALC来变换画面。另外,自动光圈镜头装有光圈环,转动光圈环时,通过镜头的光通量会发生变化,光通量即光圈,一般用F表示,其取值为镜头焦距与镜头通光口径之比,即:F=f(焦距)/D(镜头实际有效口径),F值越小,则光圈越大。

摄像机镜头参数解析

镜头参数 镜头是电视监控系统中必不可少的部件,镜头与CCD摄像机配合,可以将远距离目标成像在摄像机的CCD靶面上。 镜头的种类繁多,从焦距上分类,可分为短焦距、中焦距、和焦距和变焦距镜头;从视场的大小分类,可分为广角、标准、远摄镜头;从结构上分类,还可分为固定光圈定焦镜头、手动光圈定焦镜头、自动光圈定焦镜头、手动变焦镜头、自动光圈电动变焦镜头、电动三可变镜头(指光圈、焦距、聚焦这三者均可变)等类型。由于镜头选择得合适与否,直接关系到摄像质量的优劣,因此,在实际应用中必须合理选择镜头。 1 、镜头的参数 镜头的光学特性包括成像尺寸、焦距、相对孔径和视场角等几个参数,一般在镜头所附的说明书中都有注明,以下分别介绍。 A、成像尺寸 镜头一般可分为25. 4mm(lin)、16. 9mm(2/3in)、12. 7mm(1/2in)、8.47mm (1/3in)和6.35mm(1/4in)等几种规格,它们分别对应着不同的成像尺寸,选用镜头时,应使镜头的成像尺寸与摄像机的靶面尺寸大小相吻合。表2-1列出了几种常见CCD芯片的靶面尺寸,表中单位为mm。 表1-1 几种常见CCD芯片的靶面尺寸 由表1-1可知,12. 7mm(1/2in)的镜头应配12. 7mm(1/2in)靶面的摄像机,当镜头的成像尺寸比摄像机靶面的尺寸大时,不会影响成像,但实际成像的视场角要比该镜头的标称视场角小(参见图1-1),而当镜头的成像尺寸比摄像机靶面的尺寸小时,就会影响成像,表现为成像的画面四周被镜筒遮挡,在画面的4 个角上出现黑角(参见图1-1)。

(1)镜头成像尺寸比CCD靶面尺寸大 (2)镜头成像尺寸比CCD靶面尺寸 小 图1-1 镜头成像尺寸与CCD靶面尺寸的关系 B、焦距 在实际应用中,经常会有用户提出该摄像机能看清多么远的物体或该摄像机能看清多么宽的场景等问题,这实际上由所选用的镜头的焦距来决定,因为焦距决定了摄取图像的大小,用不同焦距的镜头对同一位置的某物体摄像时,配长焦距镜头的摄像机所摄取的景物尺寸就大,反之,配短焦距镜头的摄像机所摄取的景物尺寸就小。当然,被摄物体成像的清晰度还与所选用的CCD摄像机的分辨率及监视器的分辨率有关。 理论上,任何一种镜头均可拍摄很远的物体,并在CCD靶面上成一很小的像,但受CCD单元(像素)物理尺寸的限制,当成像小到小于CCD传感器的一个像素大小时,便不再能形成被摄物体的像,即使成像有几个像素大小,该像也难以辨识为何物。 当已知被摄物体的大小及该物体到镜头距离,则可根据下两式估算所选取配镜头的焦距: f=hD/H f=vD/V 式中,D为镜头中心到被摄物体的距离;H和V分别为被摄物体的水平尺寸和垂直尺寸;v为靶面成像的高度;h为靶面成像的水平宽度。

福克斯电气系统维修手册(共28篇第3篇)

章节 412-02 暖气与通风 适用车辆:2005 Focus 目录页数 规格 规格................................................................................................................................... 412-02-2 说明与操作 暖气与通风 ........................................................................................................................ 412-02-3 暖气芯与蒸发器芯风箱 ..................................................................................................... 412-02-3 诊断与测试 暖气与通风 ........................................................................................................................ 412-02-8 拆卸与安装 鼓风机马达 ........................................................................................................................ 412-02-9 暖气芯与蒸发器芯风箱....................................................................................................... 412-02-15 暖气芯— LHD................................................................................................................... 412-02-29 分解与组装 暖气芯与蒸发器芯风箱—车辆配备:手动温度控制........................................................... 412-02-33 暖气芯与蒸发器芯风箱—车辆配备:自动温度控制........................................................... 412-02-38 08/2005 2005 Focus

监控摄像头的选择与基本参数

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Focal length焦距 焦距的定义是从镜头到底片的距离。焦距越短,聚焦平面到镜头后背的距离越短。镜头是按照焦距的长短来划分的。焦距用毫米(mm)来表示,在有些地方也用英寸(1 inche=25mm)。 对每个摄影镜头,你都必须决定一个物体在画面中有多大。例如:是否一个镜头中应该包括整个角色或只是头部和肩部?有两种方法放大五个物体在画面中的比例。你可以将摄像机靠近物体,也可以增大镜头的焦距。 焦距与物体在画面中的比例成正比关系。如果你将焦距加倍(保持摄像机与物体的距离不变),物体在画面上的大小也加倍。物体在画面上的距离与物体到镜头的距离成反比,如果将此距离加倍,物体在画面中的大小减半。 Angle of view 在你调整摄像机焦距时,angle of view会变宽或变窄。这就是为什么图面上的物体会变大或变小。当你增大焦距,angle of view会变窄;当你减小焦距,angle of view会张大。 Perspective 透视 因为有两种方法改变物体在画面上的大小,那么移动摄像机和调整焦距有什么区别呢?为什么选择这种方法击不选用另一种方法呢?答案是移动摄像机会改变透视。与距离摄像机较近的物体相比,距摄像机较远的物体相对尺寸变化速度较慢。当你改变摄像机的焦距时透视没有变化。画面上所有的物体按同一比例改变尺寸。透视可以被认为是因距离摄像机的远近不同而造成物体在画面中大小的不同。 Camera aperture 在真实的摄像机中,光圈是指以毫米为单位表示的底片的长度和宽度。不同的底片会对应的“标准”镜头的光圈与焦距的关系是不同。一个标准镜头不会产生远摄或广角效果。它接近于人眼正常的视觉效果。当光圈增大时,要增大焦距达到正常的透视效果。例如35mm像机使用50mm镜头为标准镜头,同样是50mm的镜头用在16mm像机上就会产生远摄效果,要得到正常的透视效果,16mm的像机上应使用25mm的镜头。 在Maya中只要使用不同的底片而不改变焦距,就可以验正上面的内容。 建立新像机 默认状态下,一个新的场景中会有四个摄像机:一个透视像机(persp),三个正交摄像机(top、front和side)。当用户在视图中进行翻转、移动、推拉或缩放时操作时,代名词仍在使用同一个摄像机观察场景或物体。要使用其它摄像机观察场景,首先改变视图,然后用视图菜单 ( Panels > Perspective > New)建立新摄像机。

海康摄像机型号全参数

DS-2CC11A2P(N)-IR1(IR3)(IR5) 型号 型号DS-2CC11A2P(N)-IR1(IR3)(IR5) 名称700TVL 1/3" CCD红外防水筒型摄像机 摄像机传感器类型1/3"SONY CCD 信号系统PAL/NTSC 有效像素 PAL:976(水平)×582(垂直) NTSC:976(水平)×494(垂直) 最低照度 0.001Lux @ (F1.2,AGC ON),0 Lux with IR 0.002Lux @ (F1.8,AGC ON),0 Lux with IR 快门1/50(1/60)秒至1/100,000秒 镜头 “IR1”: 6mm @ F1.8(2.8mm,3.6mm 可选) “IR3”: 12mm @ F1.8(3.6mm,6mm,8mm,16mm 可选) “IR5”:16mm @ F1.8(3.6mm,6mm,8mm,12mm 可选) 镜头接口类型M12

1.主要特性 红外功能: ?最低照度0Lux ?采用高效红外阵列,低功耗,照射距离达60m ?红外灯与倍率距离匹配算法,根据倍率及距离调节红外灯亮度,使图像达到理想的状态?内置热处理装置,降低球机内腔温度,防止球机内罩起雾 ?恒流电路设计,红外灯寿命达3万小时 系统功能: ?采用索尼高性能CCD, 图像清晰 ?精密电机驱动, 反应灵敏, 运转平稳, 精度偏差少于0.1度, 在任何速度下图像无抖动?支持RS-485控制下对HIKVISION、Pelco-P/D协议的自动识别

?支持三维智能定位功能, 配合DVR和客户端软件可实现点击跟踪和放大 ?支持多语言菜单及操作提示功能, 用户界面友好 ?支持数据断电不丢失 ?支持断电状态记忆功能, 上电后自动回到断电前的云台和镜头状态 ?支持光纤模块接入 ?支持内置温度感应器, 可显示机内温度 ?支持防雷、防浪涌、防突波 ?室外球达到IP66防护等级 ?支持3D数字降噪 ?支持RS-485线路故障诊断功能, 把故障信息, 如地址错误、波特率错误等以文字形式显示在视频画面上 ?支持曼码协议及线路故障诊断功能, 把故障信息, 如地址错误、波特率错误等以特殊字符形式显示在视频画面上 ?支持定时任务预置点/花样扫描/巡航扫描/水平扫描/垂直扫描/随机扫描/帧扫描/全景扫描等功能 ?支持密码保护功能, 防止被人恶意修改球机菜单参数 ?支持球机标题功能, 可在视频画面叠加中、英文字符 ?支持区域扫描和显示, 球机在设定的区域设定的时间内没收到控制命令就执行区域扫描, 并显示区域名称 机芯功能: ?支持自动光圈、自动聚焦、自动白平衡、背光补偿和低照度(彩色/黑白)自动/手动转换功能, 宽动态功能可选 ?支持隐私遮蔽 云台功能: ?水平方向360°连续旋转, 垂直方向-10°-90°, 支持自动翻转, 无监视盲区 ?水平预置点速度最高可达120°/s, 垂直预置点速度最高可达100°/s ?水平键控速度为0.1°-80°/s, 垂直键控速度为0.1°-60°/s ?支持256个预置位, 并具有预置点视频冻结功能 ?支持8条巡航扫描, 每条可添加32个预置点 ?支持4条花样扫描, 总记录时间大于10分钟 ?支持比例变倍功能, 旋转速度可以根据镜头变倍倍数自动调整 ?支持守望功能, 预置点/花样扫描/巡航扫描/水平扫描/垂直扫描/随机扫描/帧扫描/全景扫描可在空闲状态停留指定时间后自动调用(包括上电后进入的空闲状态) ?支持报警功能, 内置2路报警输入(7路可选,优先级可调)和2路报警输出, 支持报警联动, 可在报警后触发报警输出/调用预置点/花样扫描/巡航扫描/水平扫描/垂直扫描/随机扫描/帧扫描/

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自动光圈镜头有两类:一类是将一个视频信号及电源从摄象机输送到透镜来控制镜头上的光圈,称为视频输入型,另一类则利用摄象机上的直流电压来直接控制光圈,称为 DC输入型。自动光圈镜头上的ALC(自动镜头控制)调整用于设定测光系统,可以整个画面的平均亮度,也可以画面中最亮部分(峰值)来设定基准信号强度,供给自动光圈调整使用。一般而言,ALC已在出厂时经过设定,可不作调整,但是对于拍摄景物中包含有一个亮度极高的目标时,明亮目标物之影像可能会造成"白电平削波" 现象,而使得全部屏幕变成白色,此时可以调节ALC来变换画面。另外,自动光圈镜头装有光圈环,转动光圈环时,通过镜头的光通量会发生变化,光通量即光圈,一般用F表示,其取值为镜头焦距与镜头通光口径之比,即:F= f(焦距)/D(镜头实际有效口径),F值越小,则光圈越大。采用自动光圈镜头,对于下列应用情况是理想的选择,它们是:在诸如太阳光直射等非常亮的情况下,用自动光圈镜头可有较宽的动态范围。要求在整个视野有良好的聚焦时,用自动光圈镜头有比固定光圈镜头更大的景深。要求在亮光上因光信号导致的模糊最小时,应使用自动光圈镜头。 (4)以镜头的视场大小分类标准镜头:视角30度左右,在1/2英寸CCD摄象机中,标准镜头焦距定为12mm,在1/3英寸CCD摄象机中,标准镜头焦距定为8mm。广角镜头:视角90度以上,焦距可小于几毫米,可提供较宽广的视景。远摄镜头:视角20度以内,焦距可达几米甚至几十米,此镜头可在远距离情况下将拍摄的物体影响放大,但使观察范围变小。变倍镜头(zoom lens):也称为伸缩镜头,有手动变倍镜头和电动变倍镜头两类。可变焦点镜头(vari-focus lens):它介于标准镜头与广角镜头

监控摄像头全参数详细介绍大全

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监控摄像头全参数详细介绍大全

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