turning now in detail to the drawings , fig1 shows the starting point of this method is the transmission signal of an fmcw radar that is in the general polynomial approach of the n th order for a transmission ramp as : with t ∈[ 0 , t r ]. with this design , the coefficients m l with l = 2 , . . . , n represent the polynomial parameters , γo represents the initial phase , and t r represents the time duration of the transmission ramp . the parameter m 1 or slope that is assumed to be given , indicates the linear component m 1 = b / t , which is exclusively present in an ideal case , wherein b describes the frequency deviation of the fmcw radar system . thus in the following formula , a single reflecting point shaped object is assumed . thus , the corresponding parameters are represented in fig1 , using the example of an idealized transmission signal . thus with equation ( 1 ) the reception signal in an ideal , noise free case is then : since the determination of relative distances between objects that are moving relative to the radar sensor at approximately the same speed represents a possible use of the method described , it can be assumed that s ( t )= 2r in the following ( fig2 ). for the momentary wavelength λ ( t ), the following results at the speed of light c : 1 λ ⁡ ( t ) = f ⁡ ( t ) c = 1 c ⁢ ( f 0 + ∑ l = 1 n ⁢ m l ⁢ t l ) ⁢ ⁢ with ⁢ ⁢ f ⁡ ( t ) = 1 2 ⁢ π ⁢ ⅆ arg ⁢ { x ⁡ ( t ) } ⅆ t = f 0 + ∑ l = 1 n ⁢ m l ⁢ t l it is advantageous if the reception signal y ( t ) is mixed into a lower frequency position . the mixed reception signal q e ( t ) results as follows , from equations ( 1 ) and ( 2 ): if q e ( t ) describes a harmonic exponential function , i . e . if m l ≡ 0 with l = 2 , . . . , n , then the ideal case is present , and the transmission signal x ( t ) possesses a purely linear increase in the transmission frequency . in order to indicate the maximal deviation from this ideal transmission frequency progression , a maximal relative linear error is defined as θ ⁢ : = max t ∈ [ 0 , t r ] ⁢ | f ⁡ ( t ) - f ideal ⁡ ( t ) | f ideal ⁡ ( t )  f 0 = 0 = 1 m 1 ⁢ max t ∈ [ 0 , t r ] ⁢  ∑ l = 2 n ⁢ m l ⁢ t l - 1  with f id ( t )= f 0 + m 1 t for the ideal case . the symbol θ therefore describes a maximum deviation of the momentary frequency progression for f 0 = 0 from the linear function f id ( t )| f 0 = 0 . taking into consideration the noise term r ( t ) that is always present in real applications , the following is obtained from equation 3 , with q ( t )= q e ( t )+ r ( t ) if the complex - value noise signal r ( t ) is assumed to be white and gaussian distributed in equation 4 , for the sake of simplicity , the noise influence for a significantly large signal - to - noise ratio can also be considered as phase noise e j { overscore ( r )}( t ) , whereby { overscore ( r )}( t ) is real - valued , white , and gaussian distributed . the phase signal , which is made time - discrete with the scanning cycle t a , results from proceeding from the known ( received ) phase scanning values φ ( nt a ), the method according to the invention implements a robust estimate of the polynomial parameters m l , with l = 2 , . . . , n . in an advantageous embodiment of the invention , a robust estimate of the unknown object distance r is additionally possible . fig3 shows a block schematic in the form of a sequence schematic of the method according to the invention . the initialization 1 takes place , according to the invention , by means of a base band shift bv of l consecutive ramps of the sequence q ( n )= q ( nt a ) that results from equation ( 4 ), by means of time discretitation . the shift of a spectrum range , which can be predetermined , of q ( e jω )= f { q ( n )} into the base band is shown as an example in fig4 . the cut - off frequencies ω 1 and ω u are defined , for example , by way of the minimum and maximum distances r min and r max , which are determined by the purpose of use of the fmcw radar system : the ramp signals q k ( n ) that are formed in this manner possess a band - pass spectrum . it is advantageous that after the base band shift and the subsequent antialiasing low - pass filtering tf , the scanning cycle can be reduced by a factor k . in this connection , the factor k particularly lies between k = 30 and k = 60 . this results in advantages with regard to a reduction in effort / expense of all further partial operations . the next step or progression of the block diagram in fig3 shows the sequence of the iterations for the calculation of a correction phase term for partial compensation of non - linear frequency components in the basic band reception sequences { circumflex over ( q )} k ( i ) ( m ) with m as a time index after cycle reduction . in the further process steps , a signal sequence whose scanning cycle t a was reduced is assumed with { circumflex over ( q )} k ( i ) ( m ). of course , these process steps can also be carried out with a sequence { circumflex over ( q )} k ( i ) ( n ), whose scanning cycle t a was not reduced . within the loop that runs through in each iteration , it is advantageous if band - pass filtering of the sequences { circumflex over ( q )} k ( i ) ( m ) is located at the beginning , which is advantageously carried out as windowing in the spectrum range , whereby all the spectral coefficients outside the window are set to zero . it is advantageous if a hamming window is used as the window function . in the case of several reflecting objects , the reception signal spectrum of a single object is selected by means of the band - pass filtering . all of the other , undesired spectra are suppressed . in addition , suppression of those noise - like spectrum components that do not belong to the working component takes place . in this way , the snr can be increased after the band - pass filtering , even in the case of a single reflecting object . to calculate the band - pass filtering , it is advantageous to perform a fast fourier transformation fft of the sequences { circumflex over ( q )} k ( i ) ( m ). for this purpose , it is advantageous if the individual discrete fourier transforms { circumflex over ( q )} k ( i ) ( μ ) of the base band reception sequences { circumflex over ( q )} k ( i ) ( m ) are calculated , whereby { circumflex over ( q )} k ( i ) ( μ )= fft {{ circumflex over ( q )} k ( i ) ( m )} for k = 1 , . . . , l . the number of fft points m typically lies at up to 1000 . in the case of a reduction of the scanning cycle t a that has advantageously been performed , and prior antialiasing low - pass filtering , the fft can be carried out with a smaller number of points m of 64 to 256 . in a next iteration step , filtered base band reception sequences { overscore ( q )} k ( i ) ( m ) are calculated by means of a band - pass filter according to { overscore ( q )} k ( i ) ( μ )= w ( μ ){ circumflex over ( q )} k ( i ) ( μ ), with { overscore ( q )} k ( i ) ( μ )= fft {{ overscore ( q )} k ( i ) ( m )}, whereby w ( μ ) is a spectrum window that can be predetermined , and μ ∈[ μ u , μ 1 ] indicates the range of the spectrum window having a window center point μ max that can be predetermined , whereby , with a lower limit μ u that can be predetermined , and an upper limit μ 1 that can be predetermined . in order to determine the position of the center point μ max , the fft magnitude spectra |{ circumflex over ( q )} k ( i ) ( μ )| are averaged over the number l , and the maximum is sought from the averaged spectrum , according to the following formula : for example , for a single reflecting object , μ 1 = 0 and μ u = m − 1 . for several non - overlapping objects , the limits μ 1 and μ u must be selected so that in each instance , only the spectral component that corresponds to the object of interest is detected . subsequently , it is advantageous if the calculation of the individual inverse discrete fourier transformed { overscore ( q )} k ( i ) ( m ) of the filtered fft spectra { overscore ( q )} k ( i ) ( μ ) takes place , whereby { overscore ( q )} k ( i ) ( m )= ifft {{ overscore ( q )} k ( i ) ( μ )} for k = 1 , . . . , l . in a subsequent iteration step , the distances { tilde over ( r )} k ( i ) are estimated by means of a maximum likelihood estimating method . the estimated distances { tilde over ( r )} k ( i ) can be estimated from the polynomial coefficients { tilde over ( m )} t , k ( i ) . subsequently , the distances { tilde over ( r )} k ( i ) are averaged over l reception sequences { circumflex over ( q )} k ( n ). in a final iteration step , a reception sequence { circumflex over ( q )} k ( i = l ) ( m ) with the averaged estimated polynomial coefficients { tilde over ( m )} l is calculated as the starting point for a next iteration loop , according to q ^ k ( i + 1 ) ⁡ ( m ) = q ^ k ( i ) ⁡ ( m ) · exp ⁢ { j ⁢ 4 ⁢ π ⁢ ⁢ r ~ ( i ) c ⁢ ∑ l = 2 n ⁢ m ~ l ⁡ ( mkt a ) l } the maximum likelihood parameter estimate takes place by using the linear estimator { tilde over ( v )}= [ a t a ] − 1 a t b ( 6 ) with the vectors { tilde over ( v )}=[{ tilde over ( r )} f 0 ,{ tilde over ( r )} m 1 ,{ tilde over ( r )} m 2 , . . . ] t , b =[ φ ( 0 ), φ ( t a ), φ ( 2t a ), . . . ] t and a matrix a having the dimension l q ×( n + 1 ), whereby l q represents the length of a sequence { circumflex over ( q )} k ( i ) ( m ). the determination of the phase values φ ( nt a ) in the vector b takes place by means of a phase unwrapping method . a reduced linearity error in the downsampled base band signal sequence { circumflex over ( q )} k ( i ) ( m ) is successively achieved by means of the phase correction , and this results in a lesser estimate variance , in each instance . if the condition |{ tilde over ( r )} ( i − 1 ) −{ tilde over ( r )} ( i ) |& lt ; ε has been fulfilled after i = i iterations , final estimated values { tilde over ( r )} and { tilde over ( m )} l can be calculated from the individual intermediate results { tilde over ( r )} ( i ) and { tilde over ( m )} l ( i ) , which have been averaged over all l reception sequences in the i th iteration , in each instance , according to : in the following , it will be shown that it is possible , using the method according to the invention , to reconstruct the spectral resolution , which has been reduced as a result of the linearity error in the fmcw radar transmission signal , of the sampled , mixed reception signal q ( n ). this will be shown in exemplary manner below , using the example of two objects at different distances . the starting point is a quadratic transmission signal sequence ( chirp ) with a linearity error of θ = 5 %, whereby the simulation parameters are selected to be n = 2 , m 2 = 5 × 10 12 , snr =− 18 db , k = 40 , and m = 64 . for the other system parameters , the following table applies : parameter value minimum possible distance r min = 900 m maximum possible distance r max = 1 , 100 m ramp increase time t r = 1 ms radio fundamental frequency f 0 = 35 ghz frequency deviation b = 100 mhz sampling frequency f a = 2 mhz spectrum averaging l l = 20 spectrum averaging , total 25 × l = 500 spectrum window w ( μ ) hamming window the objects are located at the distances r 0 = 900 m and r 1 = 1 , 100 m . fig5 shows the magnitude spectra | q v ( e jω )|,| q n ( e jω )| of the downsampled signal { circumflex over ( q )} k ( 0 ) ( m ) for a fixed k = 0 , . . . , l − 1 during the first iteration before ( top representation in fig5 a ) and after ( bottom representation in fig5 b ) band - pass filtering . the partial spectra , which can be easily separated , are clearly evident , whereby the bottom partial spectrum , which belongs to the object at the distance r 1 , is selected in the band - pass filtering . the top figure in fig5 b shows the range of the magnitude spectrum | q ( e jω )| of the radar reception signal that is of interest , which is established by the minimum and maximum distance ( see table ). as the result of the non - linearity in the transmission signal , the frequency lines that correspond to the two objects are smeared and can hardly be recognized . using the parameters estimated for the object at the distance r 1 , using the method according to the invention , the inherently non - linear component of this signal is now compensated , as shown in the bottom part of fig5 b . a comparison of the figures shows the clear increase in the object resolution . the small triangles in the bottom part of fig5 b characterize the positions of the frequency lines in the magnitude spectrum | q ( e jω )|, which would generate a transmission signal having a linear frequency increase . accordingly , while at least one embodiment of the present invention have been shown and described , it is to be understood that many changes and modifications may be made thereunto without departing from the spirit and scope of the invention as defined in the appended claims .